Reference no: EM132373963

Multiple Regression and Correlation Assignment -

Introduction - Regression analyses are a set of statistical techniques which allow one to assess the relationship between one dependent variable (DV) and several independent variables (IVs). Multiple regression is an extension of bi-variate regression in which several IVs are combined to predict the DV. Often, it may not be realistic to conclude that only one factor or IV influences the behavior of the DV. In such situations, a researcher needs to carefully identify those other possible factors and explicitly include them in the linear regression model.

You will use multiple regression and correlation procedures for this assignment.

Specific course competencies assessed by this assignment:

• Apply multivariate correlation and regression analysis and structural procedures using SPSS to analyze research data.
• Apply the APA style in writing the results section of a research report

Task - Conduct multiple regression and correlation by completing the tasks listed in the evaluation checklist using the comp dataset.

Tasks -

Provide informationally adequate descriptive statistics.

Identify the multiple regression or correlation hypothesis(es) in null form. Indicate whether you will perform multiple regression or multiple correlation, and why.

Describe the results of your evaluations of absence of high multicollinearity, normally distributed residual error, and no extreme outliers. Identify how you evaluated these assumptions.

Test your multiple regression or correlation null hypothesis(es). Provide the results of all tests. Make sure you use the backward elimination model.

If you obtain significant results, identify your prediction equation.

If you obtain significant results, identify the most important variable in predicting computer anxiety posttest.

Resources - These are the resources that will provide you the most help:

Green, S. B., & Salkind, N. J. (2007). Using SPSS for Windows and Macintosh: Analyzing and understanding data (5th ed.). Upper Saddle River, NJ: Prentice Hall.

Grimm, Y. G., & Yarnold, P. R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association.

Publication manual of the American Psychological Association (5th ed.). (2001). Washington, DC: American Psychological Association.

Process -

1. Download the SPSS comp dataset.

2. A study is conducted to determine if computer knowledge, trait anxiety, and student age measured at the start of a computer literacy course can reliably predict computer anxiety measured at the end of the course. Therefore, using the comp dataset, answer the following research question: Can computer anxiety posttest be predicted from a linear combination of computer knowledge pretest, trait anxiety pretest, and student age? Use the backward elimination model. In order to respond to this research question, complete the tasks identified in the evaluation checklist below. Organize your response around each of the tasks listed in the evaluation checklist (i.e., each checklist task should be a separate heading in your document). Regardless of the results of your evaluation of assumptions, proceed using the full, unaltered dataset provided.

Conclusion - In this assignment you used multiple regression and correlation procedures. You will encounter these procedures in many research articles. Additionally, you are very likely to use them in any research you conduct. Make sure you learn these procedures.

Attachment:- Multiple Regression and Correlation Assignment Files.rar