# Question: This portion of the SPSS project xam draws upon the

This portion of the SPSS project xam draws upon the knowledge and skills you acquired throughout this course by asking you to perform an SPSS analysis. Read the three case studies below and choose the appropriate statistical procedure. Using the Final Data Set, run the appropriate correlation or regressions procedure, analyze the data, and report the results in a properly formatted APA Results section.

Please be sure to include the following elements in your Results:

1) The assumption tests and their results (include graphs if you used them)

2) An adequate report of the descriptive statistics

3) The null hypothesis

4) The rationale for the chosen statistical procedure and results of the statistical procedure, including effect size and power

5) The decision regarding the null hypothesis

For the purpose of the Final submission, do not transform or change any variables if assumptions are not met. Conduct and report the most appropriate parametric procedure; simply note violations and identify the nonparametric alternative that could be conducted.

You may consider the following parametric statistical procedures to respond to the questions:

• One-sample t Test

• Dependent t Test

• Independent t Test

• One-Way ANOVA

• Two-Way ANOVA

• Repeated Measures ANOVA

• Bivariate Correlation (Pearson r and Spearman rho)

• Partial Correlation

• Bivariate Linear Regression

Case Study 1

An educational statistics professor is examining his grade book to determine the relationship and differences among a variety of assignment scores. He is examining these scores to determine if his course is effective. Every semester, the professor gives his students a pretest and a posttest to determine if they improved in their understanding of the course concepts. Thus, the first question he examines is as follows: Is there a difference in the number of points students earned on their educational statistics pretests and posttests?

Case Study 2

The professor is thinking about requiring a remedial statistics course for students who do not do well on the pretest; however, he is not sure if this would be helpful. Thus, he he wishes to determine whether prior statistical knowledge assists students in their performance on the final exam. He poses the following question: What is the relationship between pretest scores and final exam scores after controlling for cumulative GPA? He also wants to know about the relationship between pretest scores and final exam scores without the influence of the GPA.

Case Study 3

The professor also wants to determine whether there are differences in course points based on delivery environment (online, residential) and race. If he finds differences, then he may realize that,1) he will need to evaluate his course ethnic sensitivity, 2) he may be a more effective teacher in one environment than in the the other, 3) he needs to adapt some of his teaching methods, and 4) one learning environment may be more effective for one race than the other. As a result of these findings, he asks the following question: Do students differ in terms of the points they earn in the course based on race and delivery environment?

Please be sure to include the following elements in your Results:

1) The assumption tests and their results (include graphs if you used them)

2) An adequate report of the descriptive statistics

3) The null hypothesis

4) The rationale for the chosen statistical procedure and results of the statistical procedure, including effect size and power

5) The decision regarding the null hypothesis

For the purpose of the Final submission, do not transform or change any variables if assumptions are not met. Conduct and report the most appropriate parametric procedure; simply note violations and identify the nonparametric alternative that could be conducted.

You may consider the following parametric statistical procedures to respond to the questions:

• One-sample t Test

• Dependent t Test

• Independent t Test

• One-Way ANOVA

• Two-Way ANOVA

• Repeated Measures ANOVA

• Bivariate Correlation (Pearson r and Spearman rho)

• Partial Correlation

• Bivariate Linear Regression

Case Study 1

An educational statistics professor is examining his grade book to determine the relationship and differences among a variety of assignment scores. He is examining these scores to determine if his course is effective. Every semester, the professor gives his students a pretest and a posttest to determine if they improved in their understanding of the course concepts. Thus, the first question he examines is as follows: Is there a difference in the number of points students earned on their educational statistics pretests and posttests?

Case Study 2

The professor is thinking about requiring a remedial statistics course for students who do not do well on the pretest; however, he is not sure if this would be helpful. Thus, he he wishes to determine whether prior statistical knowledge assists students in their performance on the final exam. He poses the following question: What is the relationship between pretest scores and final exam scores after controlling for cumulative GPA? He also wants to know about the relationship between pretest scores and final exam scores without the influence of the GPA.

Case Study 3

The professor also wants to determine whether there are differences in course points based on delivery environment (online, residential) and race. If he finds differences, then he may realize that,1) he will need to evaluate his course ethnic sensitivity, 2) he may be a more effective teacher in one environment than in the the other, 3) he needs to adapt some of his teaching methods, and 4) one learning environment may be more effective for one race than the other. As a result of these findings, he asks the following question: Do students differ in terms of the points they earn in the course based on race and delivery environment?

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