SPSS HOMEWORK: BIVARIATE LINEAR REGRESSION ASSIGNMENT

SPSS HOMEWORK: BIVARIATE LINEAR REGRESSION ASSIGNMENT

INSTRUCTIONS

OVERVIEW

This assignment is designed to increase your statistical literacy and proficiency in conducting

and interpreting a bivariate linear regression analysis. You will be completing two bivariate

linear regression analyses in SPSS, using data that are related to specific research scenarios in the

behavioral sciences, such as psychology, social work, and counseling. You will also be

completing one Cumulative Knowledge Question that will use an analysis learned in a previous

week. Behind the scenes knowledge of how this test is conducted is fundamental to being able to

understand and apply research in your related field to your practice. Additionally, SPSS skills are

professionally valuable, as it is one of the most commonly used statistical software packages in

behavioral science settings, both academic and professional.

INSTRUCTIONS

• This assignment includes two problem sets that contain research scenarios and related

questions.

• For each scenario, you will run an analysis in SPSS. The required product will include

the SPSS output, an APA-style Results section describing the results, and the appropriate

graph inserted as a Figure in APA style.

• For each scenario, you will create a new SPSS data file with the data from the problem

scenario. ALL variable names in your SPSS data files must include your initials, so that

they show up in your SPSS output and graph. For example, for someone with the initials

ABC creating a variable of memory scores, the variable could be named

“ABC_mem_scores” or “Mem_Scores_ABC”, etc.

• For all problems, interpret results based on an alpha level of a = .05.

Please review the Watch: SPSS Homework Tutorial: Linear Regression in this module for

directions on how to run the statistical test, as well as the Watch: Results Sections in APA

Style for Linear Regression, which includes a template for completing an APA-style Results

section for a bivariate linear regression analysis.