Advanced Statistics for Clinical Science Assignment-
In this assignment, you will explore and apply the concepts of bivariate and multivariate regression. Using the datasets you are asked to create, complete each of the following questions and run the appropriate SPSS commands for each procedure.
Part I. Design an appropriate research study (with at least 75 participants) and create Excel and SPSS data files that fit the statistical model of bivariate regression.
1. What is your research question? Why is a bivariate regression appropriate to answer your research question?
2. Provide a statistical, symbolic, and substantive hypothesis for your research study.
3. Choose your a priori alpha level and indicate whether you used a 1-tailed or 2-tailed test.
4. List and operationally define your predictor and criterion variable. Which variableis the predictor? Which variableis the criterion?
5. What are the levels or scales of measurement for your predictor and criterion variables?
6. Compute an a priori power analysis with G*Power. Please take a screenshot of your analysis and include it with your submission of the assignment.
7. What are the basic assumptions for bivariate regression? Does your data meet these basic assumptions? Why or why not.
8. Compute the Pearson Product Moment Correlation Coefficient in Excel and match the value in SPSS.
9. Compute the b for your predictor in Excel and match the value in SPSS.
10. Compute the a in Excel and match the value in SPSS.
11. Compute the Beta in Excel and match the value in SPSS.
12. Compute the F-ratio in Excel and match the value in SPSS.
13. Compute the t for your predictor in Excel and match the value in SPSS.
14. Compute the 95% confidence interval for your regression line in Excel and match the value in SPSS.
15. Write your statistical finding and conclusion statement in APA format. See examples posted to Blackboard Learn.
Part II. Design an appropriate research study (with at least 75 participants) and create Excel and SPSS data files that fit the statistical model of a (2-predictor) multiple regression.
1. What is your research question? Why is a multiple regression appropriate to answer your research question?
2. Provide a statistical, symbolic, and substantive hypothesis for your research study.
3. Choose your a priori alpha level and indicate whether you used a 1-tailed or 2-tailed test.
4. List and operationally define your predictors and criterion variable. Which variablesare the predictors? Which variable is the criterion?
5. What are the levels or scales of measurement for your predictor and criterion variables?
6. Compute an a priori power analysis with G*Power. Please take a screenshot of your analysis and include it with your submission of the assignment.
7. What are the basic assumptions for multiple regression? Does your data meet these basic assumptions? Why or why not.
8. Compute the Multiple-R2 for in Excel and match the value in SPSS.
9. Compute the b for each predictor in Excel and match the value in SPSS.
10. Compute the a in Excel and match the value in SPSS.
11. Compute the Beta for each predictor in Excel and match the value in SPSS.
12. Compute the partial correlation coefficients for each predictor in Excel and match the value in SPSS.
13. Compute the semi-partial correlation coefficients for each predictor in Excel and match the value in SPSS.
14. Compute the F-ratio in Excel and match the value in SPSS.
15. Compute the standard error for the b of each predictor in Excel and match the value in SPSS.
16. Compute the t for each of your predictors in Excel and match the value in SPSS.
17. Write your statistical finding and conclusion statement in APA format. See examples posted to Blackboard Learn.
Attachment:- Assignment.rar