New Semester Started Get 50% OFF Study Help! --h --m --s Claim Now

Question Answers

Textbooks

Find textbooks, questions and answers

Oops, something went wrong!

Change your search query and then try again

Result Not Found

Books FREE
Study Help
Tutors
AI Study Planner NEW
Sell Books

Search
Sign In
Register

study help
business
a course in statistics with r

Statistical Methods For Psychology 7th Edition David C. Howell - Solutions

What is the optimal model calculated in Exercise 17.7?
Now run the analyses using SPSS HILOGLINEAR to solve for an optimal model using backward deletion.
Run the loglinear analysis using the saturated model and draw conclusions
Examine the table of cell frequencies and predict what terms must be in the model to explain the pattern of differences.
Maimaris, Summer, Browning, and Palmer (1994) reported on a study of head injuries in children and adults involved in bicycle accidents. They broke down the data on the basis of Age, whether a motor vehicle was involved, whether the rider was wearing a helmet, and whether there was a head injury.
Use SPSS HILOGLINEAR to derive the optimal model for the data in Exercise 17.1 using backward elimination. (Hint: use LogLinear/Model Selection from the menus.) Then reproduce the results using specific models found in Exercise 17.1. Compute and interpret coefficients for the most appropriate model.
In Exercise 17.1 Intercourse is the obvious dependent variable. What is the difference between the roles played by the Gender 3 Race interaction and the Gender 3 Intercourse interaction?
Allison (1991) offers an interesting example from a study by Morgan and Techman (1988)looking at race, gender, and the sexual intercourse for a sample of 15- and 16-year olds. The data follow.Intercourse Race Gender Yes No White Male 43 134 Female 26 149 Black Male 29 23 Female 22 36 What are the
Make up or find an example with respect to Exercise 16.25 where the slope is not nearly 1.0.Analyze it using both the analysis of covariance and a t test on difference scores. Do either of these analyses make sense?
I said that in any experiment where we have pretest and posttest scores we could either look at the difference scores (compared across groups) or use the pretest as a covariate. These two analyses will be equivalent only when the slope relating posttest to pretest scores is 1.00. How likely do you
I initially thought of creating an analysis of variance example from the example in Chapter 14, Section 14.7. I could have used Sex and Group as the independent variables, posttest scores as the dependent variable, and pretest scores as the covariate (ignoring FU6 and FU12 entirely). This would
Write up the results of Everitt’s experiment, including effect sizes.
Everitt reported data on a study of three treatments for anorexia in young girls. One treatment was cognitive behavior therapy, a second was a control condition with no therapy, and a third was a family therapy condition. These are the same data we examined in Chapter 14.The data follow.a. Run an
Use the data from Mireault (1990) in the file named Mireault.dat referred to in Exercise 7.6 to run a two-way analysis of variance on the Global Symptom Index T score (GSIT) using Gender and Group as independent variables. Plot out the cell means and interpret the results.
Use the data set named in Epinuneq.dat on the instructor’s disk to examine the results of the study by Introini-Collison and McGaugh (1986) described prior to Exercises 11.28–11.31.Using any statistical package, run a two-way analysis of variance with unequal sample sizes. What would you
Klemchuk, Bond, and Howell (1990) examined role-taking in children. Children were administered a battery of role-taking tasks. They were classified as being in daycare or not being in daycare, and as ages 2–3 or ages 4–5. The hypothesis was that children with daycare experience would perform
Compute the energy savings per household for the data in Exercise 16.16 by subtracting this year’s bill from last year’s bill. Then run an analysis of variance on the savings scores and compare that to the analysis of covariance.
In studying the energy consumption of families, we have broken them into three groups.Group 1 consists of those who have enrolled in a time-of-day electrical-rate system (the charge per kilowatt-hour of electricity is higher during peak demand times of the day). Group 2 is made up of those who
If you have access to SAS, use that program to analyze the data in Exercise 16.7.Add /SS1 SS2 SS3 SS4 to the end of your Model command and show thata. Type I sums of squares adjust each term in the model only for those that come earlier in the model statement.b. Type II sums of squares adjust main
Draw a Venn diagram representing the sums of squares in Exercise 16.7.1.2306A1 2 3.7167B1 2 0.3500B2 1 0.4778AB11 2 0.5444AB12 1 13.6750 1.1667A1 2 3.1667B1 2 0.1667B2 1 0.8333AB11 2 0.1667AB12 1 13.4167 SSSES SSreg(b) = 379.3325 SSreg(ab) = 15.8132 SSreg(b) = 379.3325 SSreg(a,ab) = 112.3392
Using the following data, demonstrate that Method I (the method advocated in this chapter)really deals with unweighted means.B1 B2 5 11 3 9 A1 14 611 910 6 11 2 A2 12 7
For the data in Exercise 16.7, the complete model isa. Show that this model reproduces the treatment and interaction effects as calculated in Table 16.3.
For the data in Exercise 16.5, the complete model isa. Show that this model reproduces the treatment and interaction effects as calculated by the method shown in Table 16.2.
Using only the SES predictors for the data in Exercise 16.7, we find .Why is this not the same as in Exercise 16.7?
Using the SES portion of the design matrix as our predictor, we find that.a. Why is this value the same as in the answer to Exercise 16.5?b. Will this be the case in all analyses of variance?
A psychologist was concerned with the relationship between Gender, Socioeconomic Status(SES), and perceived Locus of Control. She took eight adults (age 5 25 to 30 years) in each Gender–SES combination and administered a scale dealing with Locus of Control (a high score indicates that the
Taking the data from Exercise 16.1, add the scores 5 and 8 to the Average group and the scores 2, 3, 3, and 5 to the Good group. Rerun the analysis for Exercise 16.1 using the more complete data.
For the data in Exercise 16.1,a. Calculate treatment effects and show that the regression model reproduces these treatment effects.b. Demonstrate that for the regression model is equal to for the analysis of variance.
In this chapter we spent a lot of time with Guber’s study of educational expenditures and found that when we controlled for the percentage of students taking the SAT exam, Expend was not a significant predictor. However, the SAT is not a good dependent variable in discussing the quality of
Paul Jose has a Web site referred to in the section on mediation. He discusses a problem in which he believes that stress leads to depression through a mediating path via rumination.(In other words, some stressed people ruminate, and as a consequence they become depressed.) The path diagram derived
As you know, the regression coefficient gives the effect of one variable holding all other variables constant. How would you view this interpretation when you have an interaction term in your model?
In Exercise 15.4 we had a data set where BlamBeh was related to later distress at time 2.When it is included as a predictor along with Stress1 and BlamPer it is no longer a significant predictor. Why would this be likely to happen?
Malcarne, Compas, Epping, and Howell (1995) examined 126 cancer patients soon after they were diagnosed with cancer and at a four-month follow-up. At the initial interviews (Time 1)they collected data on the patients‘ current levels of distress (Distress1), the degree to which they attributed the
I was surprised to see that frequency of the behavior was not related to the likelihood of reporting. Can you suggest reasons why this might be so?
Repeat Exercise 15.31 but this time use just the dichotomous predictor Marital Status. Create a contingency table of Married/Unmarried by Report/No Report, calculate odds ratios, and compare those ratios to the results of the logistic regression. (The result will not be significant, but that is not
The data set Harass.dat contains slightly modified data on 343 cases created to replicate the results of a study of sexual harassment by Brooke and Perot (1991). The dependent variable is whether or not the subjects reported incidents of sexual harassment, and the independent variables are, in
It is useful to examine the effects of measurement reliability on the outcome of a regression problem. In Exercise 15.24 the variable PVLoss was actually a reasonably reliable variable.However, for purposes of illustration we can manufacture a new, and less reliable, measure from it by adding a bit
Repeat the analysis of Exercise 15.24, requesting statistics on regression diagnostics.a. What, if anything, do these statistics tell you about the data set?b. Delete the subject with the largest measure of influence (usually indexed by Cook’s D).What effect does that have for this particular
Notice that in the diagram in Exercise 15.27 SuppTotl has both a direct and an indirect effect on Depression. Its direct effect is the arrow that goes from SuppTotl to DepressT. The indirect effect (which here is not significant) comes from the fact that SuppTotl influences PVLoss, which in turn
In Exercise 15.24 we posited a model in which depression was a function of perceived vulnerability, social support, and age at loss. An alternative, or additional, view might be that vulnerability itself is a function of social support and age at loss. (If you lost a parent when you were very young
A compulsive researcher who wants to cover all possibilities might throw in the total score on perceived vulnerability (PVTotal) as well as PVLoss. (The total includes vulnerability to accidents, illness, and life-style related problems.)a. Run this analysis adding PVTotal to the variables used in
Use the data set Mireault.dat from Mireault (1990), described in the Appendix and found on the Web site for this book, to examine the relationship between current levels of depression and other variables. A reasonable model might propose that depression (DepressT) is a function of (1) the
For the data in Exercise 15.16, compute . How well does this equation fit compared with the optimal equation? Why should this be the case?
In Exercise 15.16 the adjusted would actually be lower for five predictors than for three predictors. Why?
In Exercise 15.16 what meaning attaches to as far as the Vermont Department of Health is concerned?
The State of Vermont is divided into 10 Health Planning Districts—they correspond roughly to counties. The following data represent the percentage of live births of babies weighing under 2500 grams (Y ), the fertility rate for females 17 years of age or younger ( ), total high-risk fertility rate
Calculate the adjusted for the 15 cases in Exercise 15.12.
Use Y and from Exercise 15.10 to show that is .
Using the data in Exercise 15.4, generate and show that .
What does the Tolerance column in Exhibit 15.6 contribute to the answers in Exercises 15.7 and 15.8?
Calculate the adjusted for the data in Exercise 15.4.
A large corporation is interested in predicting a measure of job satisfaction among its employees. They have collected data on 15 employees who each supplied information on job satisfaction, level of responsibility, number of people supervised, rating of working environment, and years of service.
For the values of in Exercise 15.2, the corresponding standard errors are[0.397 0.252.052 .025]Which, if any, predictor would you be most likely to drop if you wanted to refine your regression equation?
Refer to Exercise 15.1. Assume that b 5 [20.438 0.762.081 20.132]Interpret the results.
A psychologist studying perceived “quality of life” in a large number of cities (N 5 150)came up with the following equation using mean temperature (Temp), median income in$1000 (Income), per capita expenditure on social services (Socser), and population density(Popul) as predictors.a.
Strayer, Drews, and Crouch (2006) (which we saw as a between-subjects design in Exercise 11.32) examined the effects of cell phone use on driving ability. They had 40 drivers drive while speaking on a cell phone, drive while at the legal limit for alcohol (0.08%), and drive under normal conditions.
What do you think is the importance of the fact that the “parent” who supplies the parent rating changes from child to child?
Under what conditions might you not be interested in differences among judges?
Suppose that you had no concern about the fact that one source systematically rates children higher or lower than another source. How might you evaluate reliability differently?
What do your calculations tell you about the sources of variability in this data set?
What is the reliability of this data set in terms of the intraclass correlation coefficient?
In Exercise 14.24 you probably noticed that many observations at Time 2 are missing. (This is partly because for many patients it had not yet been 3 months since the diagnosis.)a. Compare the means at Time 1 for those subjects who did, and who did not, have data at Time 2.b. If there are
In Exercise 14.24 we ignored the fact that we have pairs of subjects from the same family.a. What is wrong with doing this?b. Under what conditions would it be acceptable to ignore this problem?c. What alternative analyses would you suggest?
Everitt reported data on a study of three treatments for anorexia in young girls. One treatment was cognitive behavior therapy, a second was a control condition with no therapy, and a third was a family therapy condition. The data follow:a. Run an analysis of variance on group differences in Gain
In the data file Stress.dat, available on the Web site, are data on the stress level reported by cancer patients and their spouses at two different times—shortly after the diagnosis and 3 months later. The data are also distinguished by the gender of the respondent. As usual, a “.” indicates
Now analyze the data in Exercise 14.22 using a mixed models approach, an appropriate form for the covariance matrix. How do those results differ from the results you found in Exercise 14.22?
The following data come from Exercise 14.20 with some observations deleted. (An entry of“999” represents a missing observation.)a. Analyze these data using a standard repeated measures analysis of variance.b. How do your results differ from the results you found in Exercise 14.20?
Using the data from Exercise 14.20 use SPSS to run a mixed models analysis of variance, specifying an appropriate form for the covariance matrix, and compare the results with those you obtained in Exercise 14.20.
Foa, Rothbaum, Riggs, and Murdock (1991) ran a study comparing different treatments for posttraumatic stress disorder (PTSD). They used three groups (plus a waiting list control)One group received Stress Inoculation Therapy (SIT), another received a Prolonged Exposure (PE) treatment, and a third
Outline the summary table for an A 3 B 3 C 3 D design with repeated measures on A and B and independent measures on C and D.
The SPSS printout in Exhibit 14.2 was obtained by treating the data in Exercise 14.10 as though all variables were between-subjects variables (i.e., as though the data represented a standard three-way factorial). Show that the error terms for the correct analysis represent a partition of the error
The abbreviated printout in Exhibit 14.1 represents the analysis of the data in Exercise 14.5.a. Compare this printout with the results you obtained in Exercise 14.5.b. What does a significant F for “MEAN” tell us?c. Relate to the table of cell standard deviations.
Run simple effects on the data in Exercise 14.14 to clarify the results.
Plot the results you obtained in Exercise 14.14.
In an investigation of cigarette smoking, an experimenter decided to compare three different procedures for quitting smoking (tapering off, immediate stopping, and aversion therapy).She took five subjects in each group and asked them to rate (on a 10-point scale) their desire to smoke “right
Suppose we had instructed our subjects to limit their summaries to 10 words. What effect might that have on the data in Exercise 14.10?
Calculate the within-groups covariance matrices for the data in Exercise 14.10.
Refer to Exercise 14.10.a. Calculate the simple effect of reading ability for children.b. Calculate the simple effect of items for adult good readers.
In a study of the way children and adults summarize stories, we selected 10 fifth graders and 10 adults. These were further subdivided into equal groups of good and poor readers(on the hypothesis that good and poor readers may store or retrieve story information differently). All subjects read 10
For the data in Exercise 14.6,a. Calculate all possible simple effects after first plotting the results.b. Test the simple effects, calculating test terms and adjusted degrees of freedom where necessary.
From the results in Exercise 14.7, do we appear to have reason to believe that we have met the assumptions required for the analysis of repeated measures?
For the data in Exercise 14.6,a. Calculate the variance–covariance matrices.b. Calculate using your answers to part (a).
For 2 years I carried on a running argument with my daughter concerning hand calculators.She wanted one. I maintained that children who use calculators never learn to do arithmetic correctly, whereas she maintained that they do. To settle the argument, we selected five of her classmates who had
To understand just what happened in the experiment involving the training of severely developmentally handicapped children (Exercise 14.3), our original experimenter evaluated a third group at the same times as he did the first two groups, but otherwise provided no special treatment. In other
An experimenter with only a modicum of statistical training took the data in Exercise 14.3 and ran an independent-groups t test instead, using the difference scores (training minus baseline) as the raw data.a. Run that analysis.b. Square the value of t and compare it to the Fs you obtained in
To demonstrate the practical uses of basic learning principles, a psychologist with an interest in behavior modification collected data on a study designed to teach self-care skills to severely developmentally handicapped children. An experimental group received reinforcement for activities related
Using the data from Exercise 14.1,a. Delete the data for the third session and run a (matched-sample) t test between Sessions 1 and 2.b. Now run a repeated-measures analysis of variance on the two columns you used in part(a) and compare this F with the preceding t.
It is at least part of the folklore that repeated experience with any standardized test leads to better scores, even without any intervening study. Suppose that we obtain eight subjects and give them a standardized admissions exam every Saturday morning for 3 weeks. The data follow:S First Second
Think of a nonstatistical example that could be used to explain to a student in an introductory statistics course why it is possible with any of the pairwise comparison tests to show that Group 1 is not different from Group 2, Group 2 is not different from Group 3, but Group 1 is different from
In the analysis of Seligman et al. (1990) data on explanatory style (Table 13.15) you will note that there are somewhat more males than females in the Optimist group and more females than males in the Pessimist group. Under what conditions might this affect the way you would want to deal with
Rerun the analysis in Exercise 13.31 but treat both variables as fixed and crossed. Show that the SSschool(code) in Exercise13.31 is the sum of SSschool and SSschool*code in this analysis. (Hint:If you run this using SPSS you will have to have both sets of schools numbered 1–7.)
An educational researcher wanted to test the hypothesis that schools that implemented strict dress codes produced students with higher academic performance. She randomly selected 7 schools in the state with dress codes and 7 schools that had no dress code. She then randomly selected 10 students
A psychologist interested in esthetics wanted to compare composers from the classical period to composers from the romantic period. He randomly selected four composers from each period, played one work from each of them, and had 5 subjects rate each of them. Different subjects were used for each
Using the data from Exercise 13.28, reproduce the simple effects shown in Table 13.14.
The data for the three-way analysis of variance given in Table 13.14 are found on the Web.They are named Tab13–14.dat. The first three entries in each record represent the coding for A (Experience), B (Road), and C (Conditions). The fourth entry is the dependent variable.Use any analysis of
Obtain the Tukey test for Dosage from the analysis of variance in Exercise 13.25. Interpret the results.
In Exercise 11.30 you calculated the average of the nine cell variances. How does that answer compare to the from Exercise 13.25?
Use any statistical package to run the two-way analysis of variance on Interval and Dosage for the data in Epineq.dat. Compare the results you obtain here with the results you obtained in Chapter 11, Exercises 11.28–11.30.
In Chapter 2 we considered Sternberg’s experiment on the time it takes to report whether a test stimulus was part of a prior stimulus display. The independent variables were the number of stimuli in the display (1, 3, or 5) and whether the test stimulus had been included in the display (Yes or
To study the effects of early experience on conditioning, an experimenter raised four groups of rats in the presence of (1) no special stimuli, (2) a tone stimulus, (3) a vibratory stimulus, and (4) both a tone and a vibratory stimulus. The rats were later classically conditioned using either a

Showing 1800 - 1900 of 2302

First
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24

Step by Step Answers

Services

Sitemap
Fun
Definitions
Become Tutor
Used Textbooks
Study Help Categories
Recent Questions
Expert Questions
Campus Wear
Sell Your Books

Company Info

Security
Copyrights
Privacy Policy
Terms & Conditions
SolutionInn Fee
Scholarship
Online Quiz
Give Feedback, Get Rewards

Get In Touch

About Us
Contact Us
Career
Jobs
FAQ
Student Discount
Campus Ambassador

Secure Payment

Download Our App

© 2026 SolutionInn. All Rights Reserved