Estimating Models Using Dummy Variables

Order Description
Estimating Models Using Dummy Variables

Analyze multiple regression testing using dummy variables
• Analyze measures for multiple regression testing
• Construct research questions
• Evaluate assumptions of multiple regression testing
• Analyze assumptions of correlation and bivariate regression
• Analyze implications for social change.

Create a research question using the General Social Survey dataset that can be answered by multiple regression. Using the SPSS software, choose a categorical variable
to dummy code as one of your predictor variables.
Estimate a multiple regression model that answers your research question. Post your response to the following:
1. What is your research question?
2. Interpret the coefficients for the model, specifically commenting on the dummy variable.
3. Run diagnostics for the regression model. Does the model meet all of the assumptions? Be sure and comment on what assumptions were not met and the possible
implications. Is there any possible remedy for one the assumption violations?
Section B
1. Were all assumptions tested for?
2. Are there some violations that the model might be robust against? Why or why not?
3. Explain and provide any additional resources (i.e., web links, articles, etc.) to provide and addressing diagnostic issues.
Use the below References and more.
References
Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications.
Fox, J. (Ed.). (1991). Regression diagnostics. Thousand Oaks, CA: SAGE Publications.
Retrieved from the Walden Library databases

Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.
Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College
via the Copyright Clearance Center.
Laureate Education (Producer). (2016m). Regression diagnostics and model evaluation [Video file]. Baltimore, MD: Author
Laureate Education (Producer). (2016). Dummy variables [Video file]. Baltimore, MD: Author.