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To assess the effect that chocolate may have on attitude over time, a researcher recruits a group of participants to complete the Acme Attitude Survey (AAS), which renders a 0 to 100 score (0 = Very bad attitude . . . 100 = Very good attitude). After giving the pretest, the researcher gives each participant a large bar of chocolate. The researcher read-ministers the AAS three more times: 5 minutes after the participant eats the chocolate, 1 hour later, and 4 hours later.
Data set: Ch 09 – Exercise 10B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Attitude_0
Definition: Attitude before eating chocolate (baseline)
Type: Continuous
Variable: Attitude_1
Definition: Attitude 5 minutes after eating chocolate
Type: Continuous
Variable: Attitude_2
Definition: Attitude 1 hour after eating chocolate
Type: Continuous
Variable: Attitude_3

Definition: Attitude 4 hours after eating chocolate
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

To assess the effect that chocolate may have on attitude over time, a researcher recruits a group of participants to complete the Acme Attitude Survey (AAS), which renders a 0 to 100 score (0 = Very bad attitude . . . 100 = Very good attitude). After giving the pretest, the researcher gives each participant a large bar of chocolate. The researcher read-ministers the AAS three more times: 5 minutes after the participant eats the chocolate, 1 hour later, and 4 hours later.
Data set: Ch 09 – Exercise 10A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Attitude_0
Definition: Attitude before eating chocolate (baseline)
Type: Continuous
Variable: Attitude_1
Definition: Attitude 5 minutes after eating chocolate
Type: Continuous
Variable: Attitude_2
Definition: Attitude 1 hour after eating chocolate
Type: Continuous
Variable: Attitude_3

Definition: Attitude 4 hours after eating chocolate
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

The Zzzleep Zzzound app provides audio selections (e.g., gentle rain, ocean waves, soothing music) to help induce peaceful sleep. During the night, the app uses the camera and motion sensor to gather sleep data. If the user wakes during the night, the app senses it and plays the selected sound for 10 minutes. For the first week, the app runs without any audio to gather baseline data. Once a week, the software transmits the mean sleep time per night for that week to the sleep researcher’s database.
Data set: Ch 09 – Exercise 09B.sav
Codebook
Variable: CellPhone
Definition: Cell phone number
Type: Alphanumeric
Variable: Sleep1
Definition: Mean sleep minutes per night for Week 1 (baseline)
Type: Continuous
Variable: Sleep2
Definition: Mean sleep minutes per night for Week 2
Type: Continuous
Variable: Sleep3
Definition: Mean sleep minutes per night for Week 3
Type: Continuous

Variable: Sleep4
Definition: Mean sleep minutes per night for Week 4
Type: Continuous
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

The Zzzleep Zzzound app provides audio selections (e.g., gentle rain, ocean waves, soothing music) to help induce peaceful sleep. During the night, the app uses the camera and motion sensor to gather sleep data. If the user wakes during the night, the app senses it and plays the selected sound for 10 minutes. For the first week, the app runs without any audio to gather baseline data. Once a week, the software transmits the mean sleep time per night for that week to the sleep researcher’s database.
Data set: Ch 09 – Exercise 09A.sav
Codebook
Variable: Cell Phone
Definition: Cell phone number
Type: Alphanumeric
Variable: Sleep1
Definition: Mean sleep minutes per night for Week 1 (baseline)
Type: Continuous
Variable: Sleep2
Definition: Mean sleep minutes per night for Week 2
Type: Continuous
Variable: Sleep3
Definition: Mean sleep minutes per night for Week 3
Type: Continuous

Variable: Sleep4
Definition: Mean sleep minutes per night for Week 4
Type: Continuous
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

In an effort to improve customer satisfaction, the manager at the Acme Customer Support Call Center installed a large-screen monitor in the front of the room to run classic movies with the sound off during work hours. At the conclusion of each call, the caller is routed to respond to an automated one-question customer satisfaction survey, where the caller is prompted to do the following: Please use the buttons on your phone to rate your satisfaction with this call on a scale of 1 to 9, where 1 is for low satisfaction and 9 is for high satisfaction. The manager will gather weekly mean customer satisfaction scores for each employee before and after the activation of the movies.
Data set: Ch 09 – Exercise 08B.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Satisfaction1
Definition: Customer satisfaction score for baseline week
Type: Continuous
Variable: Satisfaction2
Definition: Customer satisfaction score for first week of video
Type: Continuous
Variable: Satisfaction3

Definition: Customer satisfaction score for second week of video

Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

In an effort to improve customer satisfaction, the manager at the Acme Customer Support Call Center installed a large-screen monitor in the front of the room to run classic movies with the sound off during work hours. At the conclusion of each call, the caller is routed to respond to an automated one-question customer satisfaction survey, where the caller is prompted to do the following: Please use the buttons on your phone to rate your satisfaction with this call on a scale of 1 to 9, where 1 is for low satisfaction and 9 is for high satisfaction. The manager will gather weekly mean customer satisfaction scores for each employee before and after the activation of the movies.
Data set: Ch 09 – Exercise 08A.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Satisfaction1
Definition: Customer satisfaction score for baseline week
Type: Continuous
Variable: Satisfaction2
Definition: Customer satisfaction score for first week of video
Type: Continuous
Variable: Satisfaction3

Definition: Customer satisfaction score for second week of video

Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

A political consultant convened a focus group to evaluate the effectiveness of two commercials promoting a candidate. Prior to running any media, the participants are asked to answer one question: Do you intend to vote for Jones in the upcoming election? The participants will respond using a scale ranging from 1 to 7 (1 = Absolutely will not vote for Jones . . . 7 = Absolutely will vote for Jones). Next, the facilitator runs a 30-second radio advertisement, promoting the candidate, after which, the participants are asked to respond to the same question using the 1 to 7 scale. Finally, the facilitator runs a 30-second video advertisement for the candidate, after which, the participants will respond to the voting intentions using the 1 to 7 scale.
Data set: Ch 09 – Exercise 07B.sav
Codebook
Variable: ID
Definition: Name
Type: Alphanumeric
Variable: Opinion1_Baseline
Definition: Likelihood of voting for Jones
Type: Continuous
Variable: Opinion2_Audio

Definition: Likelihood of voting for Jones after hearing
the radio advertisement
Type: Continuous
Variable: Opinion3_Video

Definition: Likelihood of voting for Jones after viewing the video advertisement
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

A political consultant convened a focus group to evaluate the effectiveness of two commercials promoting a candidate. Prior to running any media, the participants are asked to answer one question: Do you intend to vote for Jones in the upcoming election? The participants will respond using a scale ranging from 1 to 7 (1 = Absolutely will not vote for Jones . . . 7 = Absolutely will vote for Jones). Next, the facilitator runs a 30-second radio advertisement, promoting the candidate, after which, the participants are asked to respond to the same question using the 1 to 7 scale. Finally, the facilitator runs a 30-second video advertisement for the candidate, after which, the participants will respond to the voting intentions using the 1 to 7 scale.
Data set: Ch 09 – Exercise 07A.sav
Codebook
Variable: ID
Definition: Name
Type: Alphanumeric
Variable: Opinion1_Baseline
Definition: Likelihood of voting for Jones
Type: Continuous
Variable: Opinion2_Audio

Definition: Likelihood of voting for Jones after hearing
the radio advertisement
Type: Continuous
Variable: Opinion3_Video

Definition: Likelihood of voting for Jones after viewing the video advertisement
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Acme Bank wants to determine if a person’s age (group) is associated with a preferred bill paying method. The research team gathers data using this self-administered survey card:
Bill Paying Survey
Please check one answer for each question:
1. How old are you?
• 18–25
• 26–35
• 36–55
• 56–99
2. What method do you use most often to pay bills?
• Check
• E-pay
• Other
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 01A.sav
Codebook
Variable: Age
Definition: Age of the respondent
Type: Categorical (1 = 18 – 25, 2 = 26 – 26, 3 = 36 – 55, 4 = 56 – 99)
Variable: BillPay
Definition: Preferred method for paying bills
Type: Categorical (1 = Check, 2 = E-pay, 3 = Other)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

On Tuesday morning, the student council at a middle school announced its plan to combat the chronic litter problem in the outdoor lunch area: The 16 large trash cans in the lunch area now each have the name of a popular band on them—they are now referred to as Band-Cans. The Band-Can containing the most trash at the end of each day wins; music from that band’s latest release will be played on the school’s public address system in between classes for the next day. The Band-Cans are 42 inches tall; at the end of each day, starting on Monday (to gather baseline data), the members of the student council will use a tape measure to record how full each Band-Can is (0 = Empty . . . 42 = Full).
Data set: Ch 09 – Exercise 06A.sav
Codebook
Variable: Band
Definition: Name of band on trash can
Type: Alphanumeric
Variable: Monday
Definition: Inches of trash in trash can (baseline)
Type: Continuous
Variable: Tuesday
Definition: Inches of trash in trash can
Type: Continuous

Variable: Wednesday
Definition: Inches of trash in trash can
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

On Tuesday morning, the student council at a middle school announced its plan to combat the chronic litter problem in the outdoor lunch area: The 16 large trash cans in the lunch area now each have the name of a popular band on them—they are now referred to as Band-Cans. The Band-Can containing the most trash at the end of each day wins; music from that band’s latest release will be played on the school’s public address system in between classes for the next day. The Band-Cans are 42 inches tall; at the end of each day, starting on Monday (to gather baseline data), the members of the student council will use a tape measure to record how full each Band-Can is (0 = Empty . . . 42 = Full).
Data set: Ch 09 – Exercise 06B.sav
Codebook
Variable: Band
Definition: Name of band on trash can
Type: Alphanumeric
Variable: Monday
Definition: Inches of trash in trash can (baseline)
Type: Continuous
Variable: Tuesday
Definition: Inches of trash in trash can
Type: Continuous

Variable: Wednesday
Definition: Inches of trash in trash can
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Acme Bank wants to determine if a person’s age (group) is associated with a preferred bill paying method. The research team gathers data using this self-administered survey card:
Bill Paying Survey
Please check one answer for each question:
1. How old are you?
• 18–25
• 26–35
• 36–55
• 56–99
2. What method do you use most often to pay bills?
• Check
• E-pay
• Other
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 01B.sav
Codebook
Variable: Age
Definition: Age of the respondent
Type: Categorical (1 = 18 – 25, 2 = 26 – 26, 3 = 36 – 55, 4 = 56 – 99)
Variable: BillPay
Definition: Preferred method for paying bills
Type: Categorical (1 = Check, 2 = E-pay, 3 = Other)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

In an effort to affordably boost productivity, the Acme Company has started providing free unlimited gourmet coffee to all employees. The manager will track the weekly total productivity (units produced) of each employee before and after the coffee machine is installed.
Data set: Ch 09 – Exercise 05B.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Productivity_1
Definition: Number of units produced during Week 1 (baseline)
Type: Continuous

Variable: Productivity_2
Definition: Number of units produced during Week 2
Type: Continuous
Variable: Productivity_3
Definition: Number of units produced during Week 3
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

In an effort to affordably boost productivity, the Acme Company has started providing free unlimited gourmet coffee to all employees. The manager will track the weekly total productivity (units produced) of each employee before and after the coffee machine is installed.
Data set: Ch 09 – Exercise 05A.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Productivity_1
Definition: Number of units produced during Week 1 (baseline)
Type: Continuous

Variable: Productivity_2
Definition: Number of units produced during Week 2
Type: Continuous
Variable: Productivity_3
Definition: Number of units produced during Week 3
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

The staff of the Physical Education Department wants to know if providing a single 15-minute individual coaching session with an expert bowler will enhance students’ bowling scores. Each participant will bowl one game, during which time the coach will unobtrusively observe his or her bowling style. Then, the coach will provide a 15-minute coaching session. Immediately following the coaching, the student will bowl a second game. One week later, the student will return to bowl a third game. The scores from all three games of each student will be recorded and evaluated to determine the effectiveness of this form of coaching.
Data set: Ch 09 – Exercise 04B.sav
Codebook
Variable: Student
Definition: Student’s last name
Type: Alphanumeric
Variable: Game1
Definition: Bowling score on first (baseline) game
Type: Continuous
Variable: Game2
Definition: Bowling score on second game
Type: Continuous
Variable: Game3
Definition: Bowling score on third game
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

The staff of the Physical Education Department wants to know if providing a single 15-minute individual coaching session with an expert bowler will enhance students’ bowling scores. Each participant will bowl one game, during which time the coach will unobtrusively observe his or her bowling style. Then, the coach will provide a 15-minute coaching session. Immediately following the coaching, the student will bowl a second game. One week later, the student will return to bowl a third game. The scores from all three games of each student will be recorded and evaluated to determine the effectiveness of this form of coaching.
Data set: Ch 09 – Exercise 04A.sav
Codebook
Variable: Student
Definition: Student’s last name
Type: Alphanumeric
Variable: Game1
Definition: Bowling score on first (baseline) game
Type: Continuous
Variable: Game2
Definition: Bowling score on second game
Type: Continuous
Variable: Game3
Definition: Bowling score on third game
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

The staff at a mental health clinic wants to determine if their current form of short-term therapy substantially reduces depression. Prior to the first treatment, each patient will be asked to complete the Acme Depression Inventory (ADI), which renders a score from 0 to 75 (0 = Low depression . . . 75 = High depression). Patients will be asked to complete the same instrument at the conclusion of their appointment on Week 5 and at the end of their final appointment on Week 10.
Data set: Ch 09 – Exercise 03B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Baseline
Definition: Acme Depression Inventory score at baseline
Type: Continuous
Variable: Week05
Definition: Acme Depression Inventory score at Week 5
Type: Continuous
Variable: Week10
Definition: Acme Depression Inventory score at Week 10
Type: Continuous

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Prior to a Heart Health presentation, you administer a survey asking participants to indicate how many times they used the stairs (as opposed to the elevator) in the past week. A week after the lecture, you resurvey the attendees. Finally, 2 weeks after the lecture, you resurvey the attendees (a third time).
Data set: Ch 09 – Exercise 02B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Time1
Definition: Number of times the steps were used in the week before the seminar
Type: Continuous
Variable: Time2
Definition: Number of times the steps were used in the week after the seminar
Type: Continuous
Variable: Time3

Definition: Number of times the steps were used in the week 2 weeks after the seminar
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Prior to a Heart Health presentation, you administer a survey asking participants to indicate how many times they used the stairs (as opposed to the elevator) in the past week. A week after the lecture, you resurvey the attendees. Finally, 2 weeks after the lecture, you resurvey the attendees (a third time).
Data set: Ch 09 – Exercise 02A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Time1
Definition: Number of times the steps were used in the week before the seminar
Type: Continuous
Variable: Time2
Definition: Number of times the steps were used in the week after the seminar
Type: Continuous
Variable: Time3

Definition: Number of times the steps were used in the week 2 weeks after the seminar
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Acme Industries has implemented a new website for employees to enter their weekly hours (e.g., start time, end time, sick hours, vacation hours, holiday hours, family leave hours). Upon clicking Save, the system checks the validity of the entries and points the user to correct any errors or omissions before saving the data. To evaluate the efficiency of this new website, the system journals the access time (in seconds) indicating how long it took for each employee to file their daily entries. A manager will assess the mean access times starting at the initial launch of the website (Week1) and continue to gather data for an additional 2 weeks (Week2 and Week3).
Data set: Ch 09 – Exercise 01B.sav
Codebook
Variable: ID
Definition: Employee ID
Type: Alphanumeric
Variable: Week1
Definition: Average time (in seconds) required to fill out webpage for first week
Type: Continuous
Variable: Week2

Definition: Average time (in seconds) required to fill out webpage for second week
Type: Continuous
Variable: Week3
Definition: Average time (in seconds) required to fill out webpage for third week
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

Acme Industries has implemented a new website for employees to enter their weekly hours (e.g., start time, end time, sick hours, vacation hours, holiday hours, family leave hours). Upon clicking Save, the system checks the validity of the entries and points the user to correct any errors or omissions before saving the data. To evaluate the efficiency of this new website, the system journals the access time (in seconds) indicating how long it took for each employee to file their daily entries. A manager will assess the mean access times starting at the initial launch of the website (Week1) and continue to gather data for an additional 2 weeks (Week2 and Week3).
Data set: Ch 09 – Exercise 01A.sav
Codebook
Variable: ID
Definition: Employee ID
Type: Alphanumeric
Variable: Week1
Definition: Average time (in seconds) required to fill out webpage for first week
Type: Continuous
Variable: Week2

Definition: Average time (in seconds) required to fill out webpage for second week
Type: Continuous
Variable: Week3
Definition: Average time (in seconds) required to fill out webpage for third week
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

To assess the effect that chocolate may have on attitude, a researcher recruits a group of participants to complete the Acme Attitude Survey (AAS), which renders a 0 to 100 score (0 = very bad attitude . . . 100 = very good attitude). After giving the pretest, the researcher gives each participant a large bar of chocolate. Five minutes after the participant eats the chocolate, the researcher readministers the AAS.
Data set: Ch 08 – Exercise 10B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Attitude_0
Definition: Attitude before eating chocolate (baseline)
Type: Continuous
Variable: Attitude_1
Definition: Attitude 5 minutes after eating chocolate
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

To assess the effect that chocolate may have on attitude, a researcher recruits a group of participants to complete the Acme Attitude Survey (AAS), which renders a 0 to 100 score (0 = very bad attitude . . . 100 = very good attitude). After giving the pretest, the researcher gives each participant a large bar of chocolate. Five minutes after the participant eats the chocolate, the researcher readministers the AAS.
Data set: Ch 08 – Exercise 10A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Attitude_0
Definition: Attitude before eating chocolate (baseline)
Type: Continuous
Variable: Attitude_1
Definition: Attitude 5 minutes after eating chocolate
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The Zzzleep Zzzound app provides audio selections (e.g., gentle rain, ocean waves, soothing music) to help induce peaceful sleep. During the night, the app uses the camera and motion sensor to gather sleep data. If the user wakes during the night, the app senses it and plays the selected sound for 10 minutes. For the first week, the app runs without any audio to gather baseline data. Once a week, the software transmits the mean sleep time per night for that week to the sleep researcher’s database.
Data set: Ch 08 – Exercise 09B.sav
Codebook
Variable: CellPhone
Definition: Cell phone number
Type: Alphanumeric
Variable: Sleep1
Definition: Mean sleep minutes per night for Week 1 (baseline)
Type: Continuous
Variable: Sleep2
Definition: Mean sleep minutes per night for Week 2
Type: Continuous
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The Zzzleep Zzzound app provides audio selections (e.g., gentle rain, ocean waves, soothing music) to help induce peaceful sleep. During the night, the app uses the camera and motion sensor to gather sleep data. If the user wakes during the night, the app senses it and plays the selected sound for 10 minutes. For the first week, the app runs without any audio to gather baseline data. Once a week, the software transmits the mean sleep time per night for that week to the sleep researcher’s database.
Data set: Ch 08 – Exercise 09A.sav
Codebook
Variable: CellPhone
Definition: Cell phone number
Type: Alphanumeric
Variable: Sleep1
Definition: Mean sleep minutes per night for Week 1 (baseline)
Type: Continuous
Variable: Sleep2
Definition: Mean sleep minutes per night for Week 2
Type: Continuous
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

In an effort to improve customer satisfaction, the manager at the Acme Customer Support Call Center installed a large-screen monitor in the front of the room to run classic movies with the sound off during work hours. At the conclusion of each call, the caller is routed to respond to an automated one-question customer satisfaction survey, where the caller is prompted with the following instructions: Please use the buttons on your phone to rate your satisfaction with this call on a scale of 1 to 9, where 1 is for low satisfaction and 9 is for high satisfaction. The manager will gather weekly mean customer satisfaction scores for each employee before and after the activation of the movies.
Data set: Ch 08 – Exercise 08B.sav
Codebook
Variable: Name
Definition: Employee name

Type: Alphanumeric
Variable: Satisfaction1
Definition: Customer satisfaction score for baseline week
Type: Continuous
Variable: Satisfaction2
Definition: Customer satisfaction score for first week of video
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

In an effort to improve customer satisfaction, the manager at the Acme Customer Support Call Center installed a large-screen monitor in the front of the room to run classic movies with the sound off during work hours. At the conclusion of each call, the caller is routed to respond to an automated one-question customer satisfaction survey, where the caller is prompted with the following instructions: Please use the buttons on your phone to rate your satisfaction with this call on a scale of 1 to 9, where 1 is for low satisfaction and 9 is for high satisfaction. The manager will gather weekly mean customer satisfaction scores for each employee before and after the activation of the movies.
Data set: Ch 08 – Exercise 08A.sav
Codebook
Variable: Name
Definition: Employee name

Type: Alphanumeric
Variable: Satisfaction1
Definition: Customer satisfaction score for baseline week
Type: Continuous
Variable: Satisfaction2
Definition: Customer satisfaction score for first week of video
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

A political consultant convened a focus group to evaluate the effectiveness of a commercial promoting a candidate. Prior to running any media, the participants are asked to answer one question: Do you intend to vote for Jones in the upcoming election? The participants will respond using a scale ranging from 1 to 7 (1 = Absolutely will not vote for Jones . . . 7 = Absolutely will vote for Jones). Next, the facilitator runs a 30-second radio advertisement, promoting the candidate, after which, the participants are asked to respond to the same question using the 1 to 7 scale.
Data set: Ch 08 – Exercise 07B.sav
Codebook
Variable: ID
Definition: Name
Type: Alphanumeric
Variable: Opinion1_Baseline
Definition: Likelihood of voting for Jones (baseline)
Type: Continuous
Variable: Opinion2_Audio
Definition: Likelihood of voting for Jones after hearing the radio advertisement
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

A political consultant convened a focus group to evaluate the effectiveness of a commercial promoting a candidate. Prior to running any media, the participants are asked to answer one question: Do you intend to vote for Jones in the upcoming election? The participants will respond using a scale ranging from 1 to 7 (1 = Absolutely will not vote for Jones . . . 7 = Absolutely will vote for Jones). Next, the facilitator runs a 30-second radio advertisement, promoting the candidate, after which, the participants are asked to respond to the same question using the 1 to 7 scale.
Data set: Ch 08 – Exercise 07A.sav
Codebook
Variable: ID
Definition: Name
Type: Alphanumeric
Variable: Opinion1_Baseline
Definition: Likelihood of voting for Jones (baseline)
Type: Continuous
Variable: Opinion2_Audio
Definition: Likelihood of voting for Jones after hearing the radio advertisement
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

On Tuesday morning, the student council at a middle school announced its plan to combat the chronic litter problem in the outdoor lunch area: The 16 large trash cans in the lunch area now each have the name of a popular band on them—they are now referred to as Band-Cans. The Band-Can containing the most trash at the end of each day wins; music from that band’s latest release will be played on the school’s public address system in between classes for the next day. The Band-Cans are 42 inches tall; at the end of each day, starting on Monday (to gather baseline data), the members of the student council will use a tape measure to record how full each Band-Can is (0 = Empty . . . 42 = Full).
Data set: Ch 08 – Exercise 06B.sav
Codebook
Variable: Band
Definition: Name of band on trashcan
Type: Alphanumeric
Variable: Monday
Definition: Inches of trash in trashcan (baseline)
Type: Continuous
Variable: Tuesday
Definition: Inches of trash in trashcan
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

On Tuesday morning, the student council at a middle school announced its plan to combat the chronic litter problem in the outdoor lunch area: The 16 large trash cans in the lunch area now each have the name of a popular band on them—they are now referred to as Band-Cans. The Band-Can containing the most trash at the end of each day wins; music from that band’s latest release will be played on the school’s public address system in between classes for the next day. The Band-Cans are 42 inches tall; at the end of each day, starting on Monday (to gather baseline data), the members of the student council will use a tape measure to record how full each Band-Can is (0 = Empty . . . 42 = Full).
Data set: Ch 08 – Exercise 06A.sav
Codebook
Variable: Band
Definition: Name of band on trashcan
Type: Alphanumeric
Variable: Monday
Definition: Inches of trash in trashcan (baseline)
Type: Continuous
Variable: Tuesday
Definition: Inches of trash in trashcan
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

In an effort to affordably boost productivity, the Acme Company has started providing free unlimited gourmet coffee to all employees. The manager will track the weekly total productivity (units produced) of each employee before and after the coffee machine is installed.
Data set: Ch 08 – Exercise 05B.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Productivity_1
Definition: Number of units produced during week 1 (baseline)
Type: Continuous
Variable: Productivity_2
Definition: Number of units produced during week 2
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

In an effort to affordably boost productivity, the Acme Company has started providing free unlimited gourmet coffee to all employees. The manager will track the weekly total productivity (units produced) of each employee before and after the coffee machine is installed.
Data set: Ch 08 – Exercise 05A.sav
Codebook
Variable: Name
Definition: Employee name
Type: Alphanumeric
Variable: Productivity_1
Definition: Number of units produced during week 1 (baseline)
Type: Continuous
Variable: Productivity_2
Definition: Number of units produced during week 2
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The staff of the Physical Education Department wants to know if providing a single 15-minute individual coaching session with an expert bowler will enhance students’ bowling scores. Each participant will bowl one game, during which time the coach will unobtrusively observe his or her bowling style. Then, the coach will provide a 15-minute coaching session. Immediately following the coaching, the student will bowl a second game. The scores of each student will be recorded and evaluated to determine the effectiveness of this form of coaching.
Data set: Ch 08 – Exercise 04B.sav
Codebook
Variable: Student
Definition: Student’s last name
Type: Alphanumeric
Variable: Game1
Definition: Bowling score on first (baseline) game
Type: Continuous

Variable: Game2
Definition: Bowling score on second game
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The staff of the Physical Education Department wants to know if providing a single 15-minute individual coaching session with an expert bowler will enhance students’ bowling scores. Each participant will bowl one game, during which time the coach will unobtrusively observe his or her bowling style. Then, the coach will provide a 15-minute coaching session. Immediately following the coaching, the student will bowl a second game. The scores of each student will be recorded and evaluated to determine the effectiveness of this form of coaching.
Data set: Ch 08 – Exercise 04A.sav
Codebook
Variable: Student
Definition: Student’s last name
Type: Alphanumeric
Variable: Game1
Definition: Bowling score on first (baseline) game
Type: Continuous

Variable: Game2
Definition: Bowling score on second game
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The staff at a mental health clinic wants to determine if their current form of short-term therapy substantially reduces depression. Prior to the first treatment, each patient will be asked to complete the Acme Depression Inventory (ADI), which renders a score from 0 to 75 (0 = Low depression . . . 75 = High depression). Patients will be asked to complete the same instrument at the conclusion of their appointmen

Data set: Ch 08 – Exercise 03B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Baseline
Definition: Acme Depression Inventory score at baseline
Type: Continuous
Variable: Week05
Definition: Acme Depression Inventory score at Week 5
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The staff at a mental health clinic wants to determine if their current form of short-term therapy substantially reduces depression. Prior to the first treatment, each patient will be asked to complete the Acme Depression Inventory (ADI), which renders a score from 0 to 75 (0 = Low depression . . . 75 = High depression). Patients will be asked to complete the same instrument at the conclusion of their appointmen

Data set: Ch 08 – Exercise 03A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Baseline
Definition: Acme Depression Inventory score at baseline
Type: Continuous
Variable: Week05
Definition: Acme Depression Inventory score at Week 5
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

Prior to a Heart Health presentation, you administer a survey asking participants to indicate how many times they used the stairs (as opposed to the elevator) in the past week. A week after the lecture, you resurvey the attendees.
Data set: Ch 08 – Exercise 02B.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Time1
Definition: Number of times the steps were used in the week before the seminar
Type: Continuous
Variable: Time2
Definition: Number of times the steps were used in the week after the seminar
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

Prior to a Heart Health presentation, you administer a survey asking participants to indicate how many times they used the stairs (as opposed to the elevator) in the past week. A week after the lecture, you resurvey the attendees.
Data set: Ch 08 – Exercise 02A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Time1
Definition: Number of times the steps were used in the week before the seminar
Type: Continuous
Variable: Time2
Definition: Number of times the steps were used in the week after the seminar
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

Acme Industries has implemented a new website for employees to enter their weekly hours (e.g., start time, end time, sick hours, vacation hours, holiday hours, family leave hours). Upon clicking Save, the system checks the validity of the entries and points the user to correct any errors or omissions before saving the data. To evaluate the efficiency of this new website, the system journals the access time (in seconds) indicating how long it took for each employee to file their daily entries. A manager will assess the mean access times starting at the initial launch of the website (Week1), and continue to gather data for the next week (Week2).
Data set: Ch 08 – Exercise 01B.sav
Codebook
Variable: ID
Definition: Employee ID
Type: Alphanumeric
Variable: Week1
Definition: Average time (in seconds) required to fill out webpage for first week
Type: Continuous
Variable: Week2
Definition: Average time (in seconds) required to fill out webpage for second week
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

Acme Industries has implemented a new website for employees to enter their weekly hours (e.g., start time, end time, sick hours, vacation hours, holiday hours, family leave hours). Upon clicking Save, the system checks the validity of the entries and points the user to correct any errors or omissions before saving the data. To evaluate the efficiency of this new website, the system journals the access time (in seconds) indicating how long it took for each employee to file their daily entries. A manager will assess the mean access times starting at the initial launch of the website (Week1), and continue to gather data for the next week (Week2).
Data set: Ch 08 – Exercise 01A.sav
Codebook
Variable: ID
Definition: Employee ID
Type: Alphanumeric
Variable: Week1
Definition: Average time (in seconds) required to fill out webpage for first week
Type: Continuous
Variable: Week2
Definition: Average time (in seconds) required to fill out webpage for second week
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality for posttest– pretest) and discuss your findings.
c. Run the paired t test and document your findings (means and Sig. [p value], hypothesis resolution).
d. Write an abstract under 200 words detailing a summary of the study, the paired t test results, hypothesis resolution, and implications of your findings.

The staff at a mental health clinic wants to determine if their current form of short-term therapy substantially reduces depression. Prior to the first treatment, each patient will be asked to complete the Acme Depression Inventory (ADI), which renders a score from 0 to 75 (0 = Low depression . . . 75 = High depression). Patients will be asked to complete the same instrument at the conclusion of their appointment on Week 5 and at the end of their final appointment on Week 10.
Data set: Ch 09 – Exercise 03A.sav
Codebook
Variable: ID
Definition: Participant ID
Type: Alphanumeric
Variable: Baseline
Definition: Acme Depression Inventory score at baseline
Type: Continuous
Variable: Week05
Definition: Acme Depression Inventory score at Week 5
Type: Continuous
Variable: Week10
Definition: Acme Depression Inventory score at Week 10
Type: Continuous

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (Mauchly’s test of sphericity) and discuss your findings.
c. Run the ANOVA repeated measures and document your findings (means and Sig. [p value]), graphical plot, and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the ANOVA repeated-measures test results, hypothesis resolution, and implications of your findings.

You notice that some bus riders wear headphones while others do not, but with so many passengers on so many different buses, it is hard to estimate if gender is a factor when it comes to wearing or not wearing headphones. To address this question, you spend the day riding city buses as you unobtrusively record your observations of each passenger on the following data sheet:

Data set: Ch 10 – Exercise 02A.sav
Codebook
Variable: Gender
Definition: Gender of bus rider
Type: Categorical (1 = Female, 2 = Male)
Variable: Headphone
Definition: Headphone status
Type: Categorical (1 = Headphones, 2 = No headphones)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstab) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

You notice that some bus riders wear headphones while others do not, but with so many passengers on so many different buses, it is hard to estimate if gender is a factor when it comes to wearing or not wearing headphones. To address this question, you spend the day riding city buses as you unobtrusively record your observations of each passenger on the following data sheet:

Data set: Ch 10 – Exercise 02B.sav
Codebook
Variable: Gender
Definition: Gender of bus rider
Type: Categorical (1 = Female, 2 = Male)
Variable: Headphone
Definition: Headphone status
Type: Categorical (1 = Headphones, 2 = No headphones)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstab) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The clinicians at Anytown Health Clinic want to determine how useful the flu shot is in their community. The researcher approaches patients as they exit the clinic; those who are willing to partake in this study are asked to sign an informed consent document and complete and submit the following card:
Flu Shot Survey
1. Did you have a flu shot this season?
□ Yes
□ No
2. Phone number or email ID:

A member of our staff will contact you in 60 days.
Thank you for participating in our survey.
□ Got sick with flu
□ Did not get sick with flu
The researcher will contact each participant in 60 days to ask if he or she contracted the flu in the past 60 days and mark the bottom of each card accordingly.
Data set: Ch 10 – Exercise 03A.sav
Codebook
Variable: FluShot
Definition: Flu shot status
Type: Categorical (1 = Had a flu shot, 2 = Did not have a flu shot)
Variable: FluSick
Definition: Flu status
Type: Categorical (1 = Got sick with flu, 2 = Did not get sick with flu)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).

d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The clinicians at Anytown Health Clinic want to determine how useful the flu shot is in their community. The researcher approaches patients as they exit the clinic; those who are willing to partake in this study are asked to sign an informed consent document and complete and submit the following card:
Flu Shot Survey
1. Did you have a flu shot this season?
□ Yes
□ No
2. Phone number or email ID:

A member of our staff will contact you in 60 days.
Thank you for participating in our survey.
□ Got sick with flu
□ Did not get sick with flu
The researcher will contact each participant in 60 days to ask if he or she contracted the flu in the past 60 days and mark the bottom of each card accordingly.
Data set: Ch 10 – Exercise 03B.sav
Codebook
Variable: FluShot
Definition: Flu shot status
Type: Categorical (1 = Had a flu shot, 2 = Did not have a flu shot)
Variable: FluSick
Definition: Flu status
Type: Categorical (1 = Got sick with flu, 2 = Did not get sick with flu)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).

d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The administrative staff of Acme College wants to optimize the availability of student resources (e.g., website content, library hours, support staffing, etc.) to better fit the needs of students. You have been asked to determine if the degree students are working on (bachelor’s vs. master’s) is associated with the type of learning (in classroom vs. remote learning) students have opted for; you are given a sample drawn from the student enrollment database to analyze.
Data set: Ch 10 – Exercise 04A.sav
Codebook
Variable: Degree
Definition: Degree that the student is currently working on

Type: Categorical (1 = Bachelor’s, 2 = Master’s)
Variable: Location
Definition: Learning modality
Type: Categorical (1 = In classroom, 2 = Remote learning)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The administrative staff of Acme College wants to optimize the availability of student resources (e.g., website content, library hours, support staffing, etc.) to better fit the needs of students. You have been asked to determine if the degree students are working on (bachelor’s vs. master’s) is associated with the type of learning (in classroom vs. remote learning) students have opted for; you are given a sample drawn from the student enrollment database to analyze.
Data set: Ch 10 – Exercise 04B.sav
Codebook
Variable: Degree
Definition: Degree that the student is currently working on

Type: Categorical (1 = Bachelor’s, 2 = Master’s)
Variable: Location
Definition: Learning modality
Type: Categorical (1 = In classroom, 2 = Remote learning)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

To determine if how data are gathered has any bearing on responses to a question involving substance abuse (Have you ever used an illegal drug?), you recruit willing participants and randomly assign them to one of three groups: Those in Group 1 will be asked the question via face-to-face interview, those in Group 2 will respond using a standard pencil-and-paper mail-in survey, and those in Group 3 will be directed to an online survey; no names or identifying information will be gathered from any of the participants.
Data set: Ch 10 – Exercise 05A.sav
Codebook
Variable: Media
Definition: Media used to administer survey
Type: Categorical (1 = Face-to-face interview, 2 = Mail in survey, 3 = Online survey)
Variable: Drug
Definition: Have you ever used an illegal drug?
Type: Categorical (1 = Yes, 2 = No)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).

d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

To determine if how data are gathered has any bearing on responses to a question involving substance abuse (Have you ever used an illegal drug?), you recruit willing participants and randomly assign them to one of three groups: Those in Group 1 will be asked the question via face-to-face interview, those in Group 2 will respond using a standard pencil-and-paper mail-in survey, and those in Group 3 will be directed to an online survey; no names or identifying information will be gathered from any of the participants.
Data set: Ch 10 – Exercise 05B.sav
Codebook
Variable: Media
Definition: Media used to administer survey
Type: Categorical (1 = Face-to-face interview, 2 = Mail in survey, 3 = Online survey)
Variable: Drug
Definition: Have you ever used an illegal drug?
Type: Categorical (1 = Yes, 2 = No)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).

d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

In an effort to better accommodate students, Acme University wants to find out if students pursuing different degrees (bachelor’s, master’s, doctorate) have the same or different preferences when it comes to class time (day, night). To determine this, you are commissioned to administer the following survey to a sample of the students currently enrolled.
Course Schedule Preference Survey
Please check one answer for each question.
1. When do you prefer to take the majority of your courses?
• Day (8.00 a.m.–5:00 p.m.)
• Night (5.00 p.m.–10:00 p.m.)
2. What degree are you currently working on?
• Bachelor’s
• Master’s
• Doctorate
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 06A.sav
Codebook
Variable: Time
Definition: Time when student takes most courses
Type: Categorical (1 = Day, 2 = Night)
Variable: Degree
Definition: Degree that the student is currently working on
Type: Categorical (1 = Bachelor’s, 2 = Master’s, 3 = Doctorate)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

In an effort to better accommodate students, Acme University wants to find out if students pursuing different degrees (bachelor’s, master’s, doctorate) have the same or different preferences when it comes to class time (day, night). To determine this, you are commissioned to administer the following survey to a sample of the students currently enrolled.
Course Schedule Preference Survey
Please check one answer for each question.
1. When do you prefer to take the majority of your courses?
• Day (8.00 a.m.–5:00 p.m.)
• Night (5.00 p.m.–10:00 p.m.)
2. What degree are you currently working on?
• Bachelor’s
• Master’s
• Doctorate
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 06B.sav
Codebook
Variable: Time
Definition: Time when student takes most courses
Type: Categorical (1 = Day, 2 = Night)
Variable: Degree
Definition: Degree that the student is currently working on
Type: Categorical (1 = Bachelor’s, 2 = Master’s, 3 = Doctorate)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

A political scientist expects that how a person votes (or does not vote) may be associated with his or her age. To investigate this, the scientist gathers a convenience sample, asking voluntary participants to anonymously complete the following card: Voter Survey
Please check one answer for each question:
1. How old are you?
□ 18–35
□ 36–64
□ 65 and older
2. How did you vote in the last election?
□ I voted in person at a polling precinct.
□ I voted by mail.
□ I did not vote.
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 07A.sav
Codebook
Variable: Age
Definition: Age classification of respondent
Type: Categorical (1 = 18−35, 2 = 36−64, 3 = 65 and older)
Variable: Vote
Definition: Method of voting
Type: Categorical (1 = Vote in person, 2 = Vote by mail, 3 = Not vote)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

A political scientist expects that how a person votes (or does not vote) may be associated with his or her age. To investigate this, the scientist gathers a convenience sample, asking voluntary participants to anonymously complete the following card: Voter Survey
Please check one answer for each question:
1. How old are you?
□ 18–35
□ 36–64
□ 65 and older
2. How did you vote in the last election?
□ I voted in person at a polling precinct.
□ I voted by mail.
□ I did not vote.
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 07B.sav
Codebook
Variable: Age
Definition: Age classification of respondent
Type: Categorical (1 = 18−35, 2 = 36−64, 3 = 65 and older)
Variable: Vote
Definition: Method of voting
Type: Categorical (1 = Vote in person, 2 = Vote by mail, 3 = Not vote)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The Acme Veterinary Nutrition Laboratory wants to find out if its three dog foods appeal to all dogs equally or if breed is a factor in a dog’s food preference. Per the research criteria specified, you recruit 90 pets: 30 cocker spaniels, 30 beagles, and 30 keeshonds. Owners are asked not to feed their pets for 4 hours prior to the test. Each dog is tested individually; the dog is placed 5 feet (1.5 meters) away from three clear bowls of dog food, all with equal weights. On cue, the leash is removed, and the dog is free to eat from any bowl(s). After dismissing each participant, you weigh the bowls; the lightest bowl wins (meaning that the dog ate the most food from that bowl). In case of a tie, the winning bowl is the one that the dog went to first.
Data set: Ch 10 – Exercise 08A.sav
Codebook
Variable: Dog
Definition: Dog breed
Type: Categorical (1 = Cocker Spaniel, 2 = Beagle, 3 = Keeshond)
Variable: Food
Definition: Dog food preference (the lightest bowl by weight)
Type: Categorical (1 = Food A, 2 = Food B, 3 = Food C)

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

The Acme Veterinary Nutrition Laboratory wants to find out if its three dog foods appeal to all dogs equally or if breed is a factor in a dog’s food preference. Per the research criteria specified, you recruit 90 pets: 30 cocker spaniels, 30 beagles, and 30 keeshonds. Owners are asked not to feed their pets for 4 hours prior to the test. Each dog is tested individually; the dog is placed 5 feet (1.5 meters) away from three clear bowls of dog food, all with equal weights. On cue, the leash is removed, and the dog is free to eat from any bowl(s). After dismissing each participant, you weigh the bowls; the lightest bowl wins (meaning that the dog ate the most food from that bowl). In case of a tie, the winning bowl is the one that the dog went to first.
Data set: Ch 10 – Exercise 08B.sav
Codebook
Variable: Dog
Definition: Dog breed
Type: Categorical (1 = Cocker Spaniel, 2 = Beagle, 3 = Keeshond)
Variable: Food
Definition: Dog food preference (the lightest bowl by weight)
Type: Categorical (1 = Food A, 2 = Food B, 3 = Food C)

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

Each year, the Department of Education in Anytown publishes a report of college-bound high school seniors. You have been recruited to compare data gathered from seniors at the Acme Academy, a local private school, with seniors at Anytown High School, a public school.
Data set: Ch 10 – Exercise 09A.sav
Codebook
Variable: HighSchool
Definition: High school
Type: Categorical (1 = Acme Academy, 2 = Anytown 289

High School)
Variable: College
Definition: College attendance
Type: Categorical (1 = Not attending university, 2 = Attending university)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

Each year, the Department of Education in Anytown publishes a report of college-bound high school seniors. You have been recruited to compare data gathered from seniors at the Acme Academy, a local private school, with seniors at Anytown High School, a public school.
Data set: Ch 10 – Exercise 09B.sav
Codebook
Variable: HighSchool
Definition: High school
Type: Categorical (1 = Acme Academy, 2 = Anytown 289

High School)
Variable: College
Definition: College attendance
Type: Categorical (1 = Not attending university, 2 =
Attending university)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Crosstabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

A political analyst is conducting a survey aimed at tuning campaign messages; the question of interest is, “Do women and men tend to vote the same or differently when it comes to electing the mayor?”
The analyst gathered responses from willing participants using self-administered survey cards:
Voter Survey—City Mayor
Please check one answer for each question:
1. What is your gender?
• Female
• Male
2. Who will you vote for?
• Smith
• Jones
• Undecided
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 10A.sav
Codebook
Variable: Gender
Definition: Respondent’s gender
Type: Categorical (1 = Female, 2 = Male)
Variable: Mayor
Definition: Vote choice for mayor
Type: Categorical (1 = Smith, 2 = Jones, 3 = Undecided)
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Cross tabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

A political analyst is conducting a survey aimed at tuning campaign messages; the question of interest is, “Do women and men tend to vote the same or differently when it comes to electing the mayor?”
The analyst gathered responses from willing participants using self-administered survey cards:
Voter Survey—City Mayor
Please check one answer for each question:
1. What is your gender?
□ Female
□ Male
2. Who will you vote for?
□ Smith
□ Jones
□ Undecided
Thank you for participating in our survey.

Data set: Ch 10 – Exercise 10A.sav
Codebook
Variable: Gender
Definition: Respondent’s gender
Type: Categorical (1 = Female, 2 = Male)
Variable: Mayor
Definition: Vote choice for mayor
Type: Categorical (1 = Smith, 2 = Jones, 3 = Undecided)
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (n is at least 5 per cell in the Cross tabs) and discuss your findings.
c. Run the chi-square test and document your findings (ns and/or percentages, Sig. [p value]).
d. Write an abstract under 200 words detailing a summary of the study, the chi-square test results, hypothesis resolution, and implications of your findings.

An exercise advocate wants to determine the effect that walking rigorously has on weight loss. The researcher recruits participants to engage in a weeklong study. The researcher instructs participants to take a brisk walk as many days of the week as possible for as long as they can. Participants will record the following data: weight prior to engaging in the walking regimen, the amount of time walked each day, and their weight at the end of the week. Participants will submit their data to the researcher at the end of the week. The researcher will preprocess the data to derive the total number of hours walked (WalkHrs) and the change in weight for each participant (WtLoss = weight at the end of the week − weight at the beginning of the week).
Data set: Ch 11 – Exercise 01A.sav
Codebook
Variable: WalkHours
Definition: Total hours walked in a week
Type: Continuous
Variable: WeightLoss
Definition: Total weight loss in a week
Type: Continuous

In Data Set A, Record 3, notice that the weight loss (WeightLoss) is −1.00; this indicates that the participant gained 1 pound. Data Set B, Record 16 also signifies a half-pound weight gain (WeightLoss = –0.50) for that participant.
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist has noticed that people seem to be spending a lot of nonwork hours on computers and wants to determine if this may, in some way, be associated with social relationship satisfaction (satisfaction derived from interacting with others). To determine if there is a correlation between nonwork computer hours and social satisfaction, the scientist recruited a group of participants and asked them to indicate (about) how many nonwork hours they spend on the computer each week. Next, each participant was given the Acme Social Satisfaction Inventory (ASSI); this self-administered instrument renders a score between 0 and 80 (0 = very low social satisfaction . . . 80 = very high social satisfaction).
Data set: Ch 11 – Exercise 02A.sav
Variable: CompHrs
Definition: Number of nonwork hours spent on the computer per week
Type: Continuous
Variable: ASSI
Definition: Acme Social Satisfaction Inventory
Type: Continuous (0 = Very low social satisfaction . . . 80 = Very high social satisfaction)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

An exercise advocate wants to determine the effect that walking rigorously has on weight loss. The researcher recruits participants to engage in a weeklong study. The researcher instructs participants to take a brisk walk as many days of the week as possible for as long as they can. Participants will record the following data: weight prior to engaging in the walking regimen, the amount of time walked each day, and their weight at the end of the week. Participants will submit their data to the researcher at the end of the week. The researcher will preprocess the data to derive the total number of hours walked (WalkHrs) and the change in weight for each participant (WtLoss = weight at the end of the week − weight at the beginning of the week).
Data set: Ch 11 – Exercise 01B.sav
Codebook
Variable: WalkHours
Definition: Total hours walked in a week
Type: Continuous
Variable: WeightLoss
Definition: Total weight loss in a week
Type: Continuous

In Data Set A, Record 3, notice that the weight loss (WeightLoss) is −1.00; this indicates that the participant gained 1 pound. Data Set B, Record 16 also signifies a half-pound weight gain (WeightLoss = –0.50) for that participant.
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist has noticed that people seem to be spending a lot of nonwork hours on computers and wants to determine if this may, in some way, be associated with social relationship satisfaction (satisfaction derived from interacting with others). To determine if there is a correlation between nonwork computer hours and social satisfaction, the scientist recruited a group of participants and asked them to indicate (about) how many nonwork hours they spend on the computer each week. Next, each participant was given the Acme Social Satisfaction Inventory (ASSI); this self-administered instrument renders a score between 0 and 80 (0 = very low social satisfaction . . . 80 = very high social satisfaction).
Data set: Ch 11 – Exercise 02B.sav
Variable: CompHrs
Definition: Number of nonwork hours spent on the computer per week
Type: Continuous
Variable: ASSI
Definition: Acme Social Satisfaction Inventory
Type: Continuous (0 = Very low social satisfaction . . . 80 = Very high social satisfaction)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist and an economist working together want to discover if there is a correlation between income and happiness. The researchers recruit a group of participants and ask them to complete a confidential survey. This self-administered survey asks for the participant’s annual income; it also includes the Acme Life Happiness Scale (ALHS), which renders a score between 0 and 100 (0 = Very unhappy . . . 100 = Very happy).
Data set: Ch 11 – Exercise 03A.sav
Variable: Income
Definition: Annual income in dollars rounded to the nearest thousand
Type: Continuous
Variable: ALHS
Definition: Score on the Acme Life Happiness Scale
Type: Continuous (0 = Very unhappy . . . 100 = Very happy)

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist and an economist working together want to discover if there is a correlation between income and happiness. The researchers recruit a group of participants and ask them to complete a confidential survey. This self-administered survey asks for the participant’s annual income; it also includes the Acme Life Happiness Scale (ALHS), which renders a score between 0 and 100 (0 = Very unhappy . . . 100 = Very happy).
Data set: Ch 11 – Exercise 03B.sav
Variable: Income
Definition: Annual income in dollars rounded to the nearest thousand
Type: Continuous
Variable: ALHS
Definition: Score on the Acme Life Happiness Scale
Type: Continuous (0 = Very unhappy . . . 100 = Very happy)

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A political scientist wants to find out if there is a correlation between listening to a newscast and an individual’s mood. This researcher recruits a group of participants and has them listen to a newscast that was recorded earlier that morning. Participants are instructed to listen for as long as they want; when they are finished listening, the researcher writes down the listening duration and then asks each participant to complete the Acme Mood Report (AMR), a selfadministered instrument that renders a score between 0 and 100 (0 = Very bad mood . . . 100 = Very good mood).
Data set: Ch 11 – Exercise 04B.sav
Variable: MinNews
Definition: Number of minutes of news listened to
Type: Continuous
Variable: AMR
Definition: Acme Mood Report
Type: Continuous (0 = Very bad mood . . . 100 = Very good mood)

a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

An educational scientist wants to examine the correlation between years of education and job satisfaction. To address this question, the scientist recruits a group of participants and has each complete a selfadministered survey; the first question asks how many years of education the participant has (e.g., 12 = high school diploma, 14 = associate’s degree, 16 = bachelor’s degree, 18 = master’s degree). The remaining questions consist of the Acme Job Satisfaction Index (AJSI), which produces a score between 0 and 60 (0 = Very unsatisfied with job . . . 60 = Very satisfied with job).
Data set: Ch 11 – Exercise 05A.sav
Variable: YearsEd
Definition: Number of years of education
Type: Continuous
Variable: AJSI
Definition: Acme Job Satisfaction Index
Type: Continuous (0 = Very unsatisfied with job . . . 60 = Very satisfied with job)
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

An educational scientist wants to examine the correlation between years of education and job satisfaction. To address this question, the scientist recruits a group of participants and has each complete a selfadministered survey; the first question asks how many years of education the participant has (e.g., 12 = high school diploma, 14 = associate’s degree, 16 = bachelor’s degree, 18 = master’s degree). The remaining questions consist of the Acme Job Satisfaction Index (AJSI), which produces a score between 0 and 60 (0 = Very unsatisfied with job . . . 60 = Very satisfied with job).
Data set: Ch 11 – Exercise 05B.sav
Variable: YearsEd
Definition: Number of years of education
Type: Continuous
Variable: AJSI
Definition: Acme Job Satisfaction Index
Type: Continuous (0 = Very unsatisfied with job . . . 60 = Very satisfied with job)
a. Write the hypotheses.

b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A dietician wants to discover if there is a correlation between age and number of meals eaten outside the home. The dietician recruits participants and administers a two-question survey: (1) How old are you? and (2) How many times do you eat out (meals not eaten at home) in an average month?

Data set: Ch 11 – Exercise 06A.sav
Variable: Age
Definition: Age of participant
Type: Continuous
Variable: MealsOut
Definition: Number of means out participant eats per month
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A dietician wants to discover if there is a correlation between age and number of meals eaten outside the home. The dietician recruits participants and administers a two-question survey: (1) How old are you? and (2) How many times do you eat out (meals not eaten at home) in an average month?

Data set: Ch 11 – Exercise 06B.sav
Variable: Age
Definition: Age of participant
Type: Continuous
Variable: MealsOut
Definition: Number of means out participant eats per month
Type: Continuous
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist wants to determine if a person’s height might be correlated with his or her sense of self-confidence. To explore this, the scientist recruits a group of participants and gathers two metrics: First the researcher administers the Acme Self-Confidence Instrument (ASCI), a self-administered survey that produces a score between 0 and 50 (0 = Very low self-confidence . . . 50 = Very high selfconfidence). Second, the scientist measures the height (in inches) of each participant.
Data set: Ch 11 – Exercise 07A.sav
Variable: Height
Definition: Height of participant (in inches)
Type: Continuous
Variable: ASCI
Definition: Acme Self-Confidence Instrument
Type: Continuous (0 = Very low self-confidence . . . 50 = Very high self-confidence)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A social scientist wants to determine if a person’s height might be correlated with his or her sense of self-confidence. To explore this, the scientist recruits a group of participants and gathers two metrics: First the researcher administers the Acme Self-Confidence Instrument (ASCI), a self-administered survey that produces a score between 0 and 50 (0 = Very low self-confidence . . . 50 = Very high selfconfidence). Second, the scientist measures the height (in inches) of each participant.
Data set: Ch 11 – Exercise 07B.sav
Variable: Height
Definition: Height of participant (in inches)
Type: Continuous
Variable: ASCI
Definition: Acme Self-Confidence Instrument
Type: Continuous (0 = Very low self-confidence . . . 50 = Very high self-confidence)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.
c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A sociologist has learned from a prior study that there is a strong positive correlation between time spent playing a video game and the score the player earns on that game (practice makes perfect). Because achieving such proficiency is time-consuming, this sociologist expects that there may be a (negative) correlation between game score and overall academic performance (grade: 0 . . . 100). To determine if there is such an inverse correlation, the sociologist recruits a group of participants to play a popular video game for 15 minutes, at which time the researcher records the score. Participants will also be asked to provide a copy of their most recent transcript.
Data set: Ch 11 – Exercise 08A.sav
Variable: Score
Definition: Score on video game
Type: Continuous
Variable: Grade
Definition: Overall academic grade
Type: Continuous (0 . . . 100)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.

c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A sociologist has learned from a prior study that there is a strong positive correlation between time spent playing a video game and the score the player earns on that game (practice makes perfect). Because achieving such proficiency is time-consuming, this sociologist expects that there may be a (negative) correlation between game score and overall academic performance (grade: 0 . . . 100). To determine if there is such an inverse correlation, the sociologist recruits a group of participants to play a popular video game for 15 minutes, at which time the researcher records the score. Participants will also be asked to provide a copy of their most recent transcript.
Data set: Ch 11 – Exercise 08B.sav
Variable: Score
Definition: Score on video game
Type: Continuous
Variable: Grade
Definition: Overall academic grade
Type: Continuous (0 . . . 100)
a. Write the hypotheses.
b. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.

c. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

In order to better control inventory, Acme Motors wants to assess how similar customer car color preference is comparing the Pico Boulevard dealership to the Sepulveda Boulevard dealership (in the data sets, the most popular car color choice is at the top of the list for each dealership).
Data set: Ch 11 – Exercise 09A.sav
Variable: Pico
Definition: Customer car color preference at the Pico Blvd. dealership
Type: Categorical (1 = Black, 2 = Blue, 3 = Red, 4 = Silver, 5 = White, 6 = Yellow)
Variable: Sepulveda
Definition: Customer car color preference at the Sepulveda
Blvd. dealership
Type: Categorical (1 = Black, 2 = Blue, 3 = Red, 4 = Silver, 5 = White, 6 = Yellow)
a. Write the hypotheses.

b. Verify the pretest checklist (both independently ranking the same set of items).
c. Run the bivariate correlation for Spearman’s rho, and document your findings (Spearman rho and Sig. [p value]) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

In order to better control inventory, Acme Motors wants to assess how similar customer car color preference is comparing the Pico Boulevard dealership to the Sepulveda Boulevard dealership (in the data sets, the most popular car color choice is at the top of the list for each dealership).
Data set: Ch 11 – Exercise 09B.sav
Variable: Pico
Definition: Customer car color preference at the Pico Blvd. dealership
Type: Categorical (1 = Black, 2 = Blue, 3 = Red, 4 = Silver, 5 = White, 6 = Yellow)
Variable: Sepulveda
Definition: Customer car color preference at the Sepulveda
Blvd. dealership
Type: Categorical (1 = Black, 2 = Blue, 3 = Red, 4 = Silver, 5 = White, 6 = Yellow)
a. Write the hypotheses.

b. Verify the pretest checklist (both independently ranking the same set of items).
c. Run the bivariate correlation for Spearman’s rho, and document your findings (Spearman rho and Sig. [p value]) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

Ariel and Dusty want to determine how similar their movie preferences are. They independently rank the 13 movie categories with their favorite at the top.
Data set: Ch 11 – Exercise 10A.sav
Variable: Ariel
Definition: Ariel’s movie type preference
Type: Categorical (1 = Action / Adventure, 2 = Animation=, 3 = Comedy, 4 = Cult Movie, 5 = Documentary, 6 = Fantasy, 7 =
Film Noir, 8 = Horror, 9 = Romantic, 10 = Sci-Fi, 11 = Spy, 12 = Western, 13 = Zombies)
Variable: Dusty
Definition: Dusty’s movie type preference
Type: Categorical (1 = Action / Adventure, 2 = Animation =, 3 = Comedy, 4 = Cult Movie, 5 = Documentary, 6 = Fantasy, 7 = Film Noir, 8 = Horror, 9 = Romantic, 10 = Sci-Fi, 11 = Spy, 12 = Western, 13 = Zombies)
a. Write the hypotheses.
b. Verify the pretest checklist (both independently ranking the same set of items).
c. Run the bivariate correlation for Spearman’s rho and document your findings (Spearman rho and Sig. [p value]) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

Ariel and Dusty want to determine how similar their movie preferences are. They independently rank the 13 movie categories with their favorite at the top.
Data set: Ch 11 – Exercise 10B.sav
Variable: Ariel
Definition: Ariel’s movie type preference
Type: Categorical (1 = Action / Adventure, 2 = Animation=, 3 = Comedy, 4 = Cult Movie, 5 = Documentary, 6 = Fantasy, 7 =
Film Noir, 8 = Horror, 9 = Romantic, 10 = Sci-Fi, 11 = Spy, 12 = Western, 13 = Zombies)
Variable: Dusty
Definition: Dusty’s movie type preference
Type: Categorical (1 = Action / Adventure, 2 = Animation =, 3 = Comedy, 4 = Cult Movie, 5 = Documentary, 6 = Fantasy, 7 = Film Noir, 8 = Horror, 9 = Romantic, 10 = Sci-Fi, 11 = Spy, 12 = Western, 13 = Zombies)
a. Write the hypotheses.
b. Verify the pretest checklist (both independently ranking the same set of items).
c. Run the bivariate correlation for Spearman’s rho and document your findings (Spearman rho and Sig. [p value]) and hypothesis resolution.
d. Write an abstract under 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings.

A public health nurse has conducted a survey of people in the community to better comprehend the effectiveness of the flu shot this season using the following survey instrument:
Flu Survey
1. Gender: □ Female □ Male
2. How old are you? _____
3. Did you have a flu shot this season? □ No □ Yes
4. Do you have any chronic disease(s)? □ No □ Yes
5. How many days were you sick with the flu this season? _____
Data set: Ch 12 – Exercise 01A.sav
Codebook
Variable: Flu_sick
Definition: [Outcome] How many days were you sick with the flu this season?
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Flu_shot
Definition: [Predictor] Did person have a flu shot this season?

Type: Categorical (0 = Got a flu shot, 1 = Did not get a flu shot)
Variable: Chronic_disease
Definition: [Predictor] Does the person have chronic disease(s)?
Type: Categorical (0 = Has chronic disease(s), 1 = No chronic disease(s))
Variable: Age
Definition: [Predictor] Age
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A public health nurse has conducted a survey of people in the community to better comprehend the effectiveness of the flu shot this season using the following survey instrument:
Flu Survey
1. Gender: □ Female □ Male
2. How old are you? _____
3. Did you have a flu shot this season? □ No □ Yes
4. Do you have any chronic disease(s)? □ No □ Yes
5. How many days were you sick with the flu this season? _____
Data set: Ch 12 – Exercise 01B.sav
Codebook
Variable: Flu_sick
Definition: [Outcome] How many days were you sick with the flu this season?
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Flu_shot
Definition: [Predictor] Did person have a flu shot this season?

Type: Categorical (0 = Got a flu shot, 1 = Did not get a flu shot)
Variable: Chronic_disease
Definition: [Predictor] Does the person have chronic disease(s)?
Type: Categorical (0 = Has chronic disease(s), 1 = No chronic disease(s))
Variable: Age
Definition: [Predictor] Age
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

This data set (Ch 12 – Exercise 01B.sav) is the same as the first data set except the Age variable has been recoded from a continuous variable that contained the actual ages to a categorical variable, now coded as Pediatric/Adult, using the following recoding criteria:
If Age < 18, then recode as 0 = Pediatric
If Age ≥ 18, then recode as 1 = Adult
The corresponding modification has been made to the codebook:
Variable: Age
Definition: [Predictor] Age
Type: Categorical (0 = Pediatric, 1 = Adult)

Acme Solar Systems wants to discover the characteristics of those who intend to install solar energy systems in their homes.
Data set: Ch 12 – Exercise 02A.sav
Codebook
Variable: Install
Definition: [Outcome] Self-reported likelihood that the person would opt for solar energy within the next 12 months.
Type: Continuous (1 = Absolutely will not . . . 10 = Absolutely will)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Income
Definition: [Predictor] Annual household income
Type: Continuous

Variable: Neighborhood
Definition: [Predictor] Type of neighborhood
Type: Categorical (0 = Urban, 1 = Rural)
Variable: Family
Definition: [Predictor] Number of people living in the household
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

Acme Solar Systems wants to discover the characteristics of those who intend to install solar energy systems in their homes.
Data set: Ch 12 – Exercise 02B.sav
Codebook
Variable: Install
Definition: [Outcome] Self-reported likelihood that the person would opt for solar energy within the next 12 months.
Type: Continuous (1 = Absolutely will not . . . 10 = Absolutely will)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Income
Definition: [Predictor] Annual household income
Type: Continuous

Variable: Neighborhood
Definition: [Predictor] Type of neighborhood
Type: Categorical (0 = Urban, 1 = Rural)
Variable: Family
Definition: [Predictor] Number of people living in the household
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A public opinion consultant is interested in the demographics of those who are in favor of capital punishment (death penalty).
Data set: Ch 12 – Exercise 03A.sav
Codebook
Variable: Death_penalty
Definition: [Outcome] Are you in favor of the death penalty?
Type: Continuous (1 = Anti-death penalty . . . 10 = Prodeath penalty)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Religion
Definition: [Predictor] Religion

Type: Categorical (0 = Atheist, 1 = Buddhist, 2 = Catholic, 3 = Hindu, 4 = Jewish, 5 = Other)
Variable: Education
Definition: [Predictor] Years of education (High school = 12, Associate’s = 14, Bachelor’s = 16, Master’s = 18,
Doctorate > 18)
Type: Continuous
This data set contains two polychotomous predictor variables (Race and Religion), which are represented by the corresponding dummycoded variables. Follow this load procedure:
1. Move Death_penalty into the Dependent box.
2. Move Age, Gender, and Education into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
6. Click Next.
7. Move Religion.1, Religion.2, Religion.3, Religion.4, and Religion.5 into the Independent(s) box.

a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A public opinion consultant is interested in the demographics of those who are in favor of capital punishment (death penalty).
Data set: Ch 12 – Exercise 03B.sav
Codebook
Variable: Death_penalty
Definition: [Outcome] Are you in favor of the death penalty?
Type: Continuous (1 = Anti-death penalty . . . 10 = Prodeath penalty)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Religion
Definition: [Predictor] Religion

Type: Categorical (0 = Atheist, 1 = Buddhist, 2 = Catholic, 3 = Hindu, 4 = Jewish, 5 = Other)
Variable: Education
Definition: [Predictor] Years of education (High school = 12, Associate’s = 14, Bachelor’s = 16, Master’s = 18,
Doctorate > 18)
Type: Continuous
This data set contains two polychotomous predictor variables (Race and Religion), which are represented by the corresponding dummycoded variables. Follow this load procedure:
1. Move Death_penalty into the Dependent box.
2. Move Age, Gender, and Education into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
6. Click Next.
7. Move Religion.1, Religion.2, Religion.3, Religion.4, and Religion.5 into the Independent(s) box.

a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

The B data set is the same as the A data set with the following modifications:
The Education variable has been recoded from a continuous variable (total number of years of education) to a categorical variable (0 = No college degree, 1 = College degree)

Acme Employment Services wants to evaluate the effectiveness of its “Get That Job” seminars, which consists of experts facilitating sessions designed to enhance resume writing, job search strategies, and interviewing techniques. After 90 days, participants are surveyed to assess their characteristics and outcomes.
Data set: Ch 12 – Exercise 04A.sav
Codebook
Variable: Employment_status
Definition: [Outcome] Number of days it took to find a job
Type: Continuous (1 . . . 90; 90 = Still looking for work)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Experience
Definition: [Predictor] Years of experience working in their current field
Type: Continuous

Variable: Applications
Definition: [Predictor] Total number of job applications submitted
Type: Continuous

This data set contains a polychotomous predictor variable (Race), which is represented by the corresponding dummy-coded variables. Follow this load procedure:
1. Move Employment_status into the Dependent box.
2. Move Gender, Experience, and Applications into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.

c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

Acme Employment Services wants to evaluate the effectiveness of its “Get That Job” seminars, which consists of experts facilitating sessions designed to enhance resume writing, job search strategies, and interviewing techniques. After 90 days, participants are surveyed to assess their characteristics and outcomes.
Data set: Ch 12 – Exercise 04B.sav
Codebook
Variable: Employment_status
Definition: [Outcome] Number of days it took to find a job
Type: Continuous (1 . . . 90; 90 = Still looking for work)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Experience
Definition: [Predictor] Years of experience working in their current field
Type: Continuous

Variable: Applications
Definition: [Predictor] Total number of job applications submitted
Type: Continuous

This data set contains a polychotomous predictor variable (Race), which is represented by the corresponding dummy-coded variables. Follow this load procedure:
1. Move Employment_status into the Dependent box.
2. Move Gender, Experience, and Applications into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.

c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A therapist at the Acme College Counseling Center noted a high prevalence of adjustment disorder among incoming freshmen, with depression being the predominate symptom. The clinicians want to determine the characteristics of those most amenable to therapy over a course of 10 sessions.
Data set: Ch 12 – Exercise 05A.sav
Codebook
Variable: Treatment_effectiveness
Definition: [Outcome] Score on the Acme Adjustment Scale
Type: Continuous (5 = Poorly adjusted . . . 40 = Well adjusted)
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Units
Definition: [Predictor] Number of units the student is enrolled in
Type: Continuous
Variable: Work

Definition: [Predictor] Number of hours of (nonacademic) work per week
Type: Continuous
Variable: Treatment_modality
Definition: [Predictor] Form of treatment
Type: Categorical (0 = Individual, 1 = Group)
Variable: Home
Definition: [Predictor] Living conditions at home

Type: Categorical (0 = Lives with family, 1 = Lives with roommate(s), 2 = Lives alone)

This data set contains a polychotomous predictor variable (Home), which is represented by the corresponding dummy-coded variables. Follow this load procedure:
1. Move Treatment_effectiveness into the Dependent box.
2. Move Gender, Age, Units, Work, and Treatment_modality into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Home.1 and Home.2 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A therapist at the Acme College Counseling Center noted a high prevalence of adjustment disorder among incoming freshmen, with depression being the predominate symptom. The clinicians want to determine the characteristics of those most amenable to therapy over a course of 10 sessions.
Data set: Ch 12 – Exercise 05B.sav
Codebook
Variable: Treatment_effectiveness
Definition: [Outcome] Score on the Acme Adjustment Scale
Type: Continuous (5 = Poorly adjusted . . . 40 = Well adjusted)
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Units
Definition: [Predictor] Number of units the student is enrolled in
Type: Continuous
Variable: Work

Definition: [Predictor] Number of hours of (nonacademic) work per week
Type: Continuous
Variable: Treatment_modality
Definition: [Predictor] Form of treatment
Type: Categorical (0 = Individual, 1 = Group)
Variable: Home
Definition: [Predictor] Living conditions at home

Type: Categorical (0 = Lives with family, 1 = Lives with roommate(s), 2 = Lives alone)

This data set contains a polychotomous predictor variable (Home), which is represented by the corresponding dummy-coded variables. Follow this load procedure:
1. Move Treatment_effectiveness into the Dependent box.
2. Move Gender, Age, Units, Work, and Treatment_modality into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Home.1 and Home.2 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A technology firm wants to determine the characteristics of potential customers for a new voice-activated home entertainment system.
Data set: Ch 12 – Exercise 06A.sav
Codebook
Variable: Purchase
Definition: [Outcome] Will the person buy this within 6 months?
Type: Continuous (0 = Will not buy it . . . 100 = Will buy it)
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Partner
Definition: [Predictor] Relational status
Type: Categorical (0 = Single, 1 = Partner)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Income
Definition: [Predictor] Annual income
Type: Continuous
Variable: Brand_ownership
Definition: [Predictor] Does the person already own any other product(s) of this brand
Type: Categorical (0 = Does not own this brand, 1 = Owns this brand)

This data set contains a polychotomous predictor variable (Race), which is represented by the corresponding dummy-coded variables.
Follow this load procedure:
1. Move Purchase into the Dependent box.
2. Move Gender, Partner, Age, Income, and Brand_ownership into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

A technology firm wants to determine the characteristics of potential customers for a new voice-activated home entertainment system.
Data set: Ch 12 – Exercise 06B.sav
Codebook
Variable: Purchase
Definition: [Outcome] Will the person buy this within 6 months?
Type: Continuous (0 = Will not buy it . . . 100 = Will buy it)
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Partner
Definition: [Predictor] Relational status
Type: Categorical (0 = Single, 1 = Partner)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Income
Definition: [Predictor] Annual income
Type: Continuous
Variable: Brand_ownership
Definition: [Predictor] Does the person already own any other product(s) of this brand
Type: Categorical (0 = Does not own this brand, 1 = Owns this brand)

This data set contains a polychotomous predictor variable (Race), which is represented by the corresponding dummy-coded variables.
Follow this load procedure:
1. Move Purchase into the Dependent box.
2. Move Gender, Partner, Age, Income, and Brand_ownership into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R2, R2 change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.

The Acme Industries Safety Supervisor wants to determine the factors that predict employees passing the annual required site safety competency training course.
Data set: Ch 13 – Exercise 10B.sav
Codebook
Variable: Test_result
Definition: [Outcome] Did the employee pass the annual safety exam?
Type: Categorical
0 = Fail
1 = Pass [←BASIS FOR MODEL]
Variable: Training_type
Definition: [Predictor] Training type
Type: Categorical
0 = Workbook [←REFERENCE]
1 = Online course
2 = Simulation lab
Variable: Years
Definition: [Predictor] Years of professional experience
Type: Continuous
Variable: Employment_hours
Definition: [Predictor] Part-time or full-time

Type: Categorical
0 = Part-time [←REFERENCE]
1 = Full-time
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

The Acme Industries Safety Supervisor wants to determine the factors that predict employees passing the annual required site safety competency training course.
Data set: Ch 13 – Exercise 10A.sav
Codebook
Variable: Test_result
Definition: [Outcome] Did the employee pass the annual safety exam?
Type: Categorical
0 = Fail
1 = Pass [←BASIS FOR MODEL]
Variable: Training_type
Definition: [Predictor] Training type
Type: Categorical
0 = Workbook [←REFERENCE]
1 = Online course
2 = Simulation lab
Variable: Years
Definition: [Predictor] Years of professional experience
Type: Continuous
Variable: Employment_hours
Definition: [Predictor] Part-time or full-time

Type: Categorical
0 = Part-time [←REFERENCE]
1 = Full-time
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

The Transplant Committee wants to gain a better understanding of those who opt to be an organ donor upon their death.
Data set: Ch 13 – Exercise 09B.sav
Codebook
Variable: Organ_donor
Definition: [Outcome] Is the person an organ donor?
Type: Categorical
0 = Not organ donor
1 = Organ donor [←BASIS FOR MODEL]
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Religion
Definition: [Predictor] Religion
Type: Categorical
0 = Atheist [←REFERENCE]
1 = Buddhist
2 = Catholic

3 = Hindu
4 = Jewish

= Other
Variable: SES
Definition: [Predictor] Socioeconomic status
Type: Categorical
0 = Lower class [←REFERENCE]
1 = Middle class
2 = Upper class
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

The Transplant Committee wants to gain a better understanding of those who opt to be an organ donor upon their death.
Data set: Ch 13 – Exercise 09A.sav
Codebook
Variable: Organ_donor
Definition: [Outcome] Is the person an organ donor?
Type: Categorical
0 = Not organ donor
1 = Organ donor [←BASIS FOR MODEL]
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Religion
Definition: [Predictor] Religion
Type: Categorical
0 = Atheist [←REFERENCE]
1 = Buddhist
2 = Catholic

3 = Hindu
4 = Jewish

= Other
Variable: SES
Definition: [Predictor] Socioeconomic status
Type: Categorical
0 = Lower class [←REFERENCE]
1 = Middle class
2 = Upper class
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

In an effort to identify the characteristics of incoming high school students who are most vulnerable to dropping out, the research staff gathered data on the senior students at the end of the school year.
Based on this data, freshmen who are identified as vulnerable to dropping out will be offered access to free comprehensive tutorial services.
Data set: Ch 13 – Exercise 08B.sav
Codebook
Variable: HS_completion
Definition: [Outcome] Did the student drop out or graduate?
Type: Categorical
0 = Graduated
1 = Drop-out [←BASIS FOR MODEL]
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Adjusted_income
Definition: [Predictor] Annual household income ÷ number of people in household

Type: Continuous
Variable: Education_parents
Definition: [Predictor] Highest years of parent’s education
Type: Continuous (e.g., High school = 12, Associate’s = 14, Bachelor’s = 16, Master’s = 18, Doctorate > 18)
Variable: Language_skill
Definition: [Predictor] Pre–high school reading and writing skills placement exam
Type: Continuous (1 . . . 30)

Variable: Math_skill
Definition: [Predictor] Pre–high school math skills placement exam
Type: Continuous (1 . . . 30)
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

In an effort to identify the characteristics of incoming high school students who are most vulnerable to dropping out, the research staff gathered data on the senior students at the end of the school year.
Based on this data, freshmen who are identified as vulnerable to dropping out will be offered access to free comprehensive tutorial services.
Data set: Ch 13 – Exercise 08A.sav
Codebook
Variable: HS_completion
Definition: [Outcome] Did the student drop out or graduate?
Type: Categorical
0 = Graduated
1 = Drop-out [←BASIS FOR MODEL]
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Adjusted_income
Definition: [Predictor] Annual household income ÷ number of people in household

Type: Continuous
Variable: Education_parents
Definition: [Predictor] Highest years of parent’s education
Type: Continuous (e.g., High school = 12, Associate’s = 14, Bachelor’s = 16, Master’s = 18, Doctorate > 18)
Variable: Language_skill
Definition: [Predictor] Pre–high school reading and writing skills placement exam
Type: Continuous (1 . . . 30)

Variable: Math_skill
Definition: [Predictor] Pre–high school math skills placement exam
Type: Continuous (1 . . . 30)
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

Acme Coffee, which currently sells gourmet coffee blends, is now considering selling a single-serve coffee maker that brews a cup of coffee in 30 seconds. They conduct a survey to help identify the characteristics of potential customers for this high-tech coffee brewer.
Data set: Ch 13 – Exercise 07B.sav
Codebook
Variable: Buy
Definition: [Outcome] Would you consider buying this coffee brewer?
Type: Categorical
0 = No
1 = Yes [←BASIS FOR MODEL]
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Acme_Coffee
Definition: [Predictor] Does the person currently drink
Acme Coffee?

Type: Categorical
0 = Doesn’t drink Acme Coffee [←REFERENCE]
1 = Drinks Acme Coffee
Variable: Income
Definition: [Predictor] Annual household income
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.

c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

Acme Coffee, which currently sells gourmet coffee blends, is now considering selling a single-serve coffee maker that brews a cup of coffee in 30 seconds. They conduct a survey to help identify the characteristics of potential customers for this high-tech coffee brewer.
Data set: Ch 13 – Exercise 07A.sav
Codebook
Variable: Buy
Definition: [Outcome] Would you consider buying this coffee brewer?
Type: Categorical
0 = No
1 = Yes [←BASIS FOR MODEL]
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Acme_Coffee
Definition: [Predictor] Does the person currently drink
Acme Coffee?

Type: Categorical
0 = Doesn’t drink Acme Coffee [←REFERENCE]
1 = Drinks Acme Coffee
Variable: Income
Definition: [Predictor] Annual household income
Type: Continuous
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.

c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

A technology firm wants to determine the characteristics of potential customers for a new voice-activated home entertainment system.
Data set: Ch 13 – Exercise 06B.sav

Codebook
Variable: Purchase
Definition: [Outcome] Will the person buy this within 6 months?
Type: Categorical
0 = Will not buy it 1 = Will buy it [←BASIS FOR MODEL]
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical
0 = Female [←REFERENCE]
1 = Male
Variable: Race
Definition: [Predictor] Race
Type: Categorical
0 = African American [←REFERENCE]
1 = Asian
2 = Caucasian
3 = Latino
4 = Other
Variable: Partner

Definition: [Predictor] Relational status
Type: Categorical
0 = Single [←REFERENCE]
1 = Partner
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Income
Definition: [Predictor] Annual income
Type: Continuous
Variable: Brand_ownership
Definition: [Predictor] Does the person already own any other product(s) of this brand
Type: Categorical
0 = Does not own this brand [←REFERENCE]
1 = Owns this brand
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.

c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

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