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In Week 9, you completed your Part 1 for this Assignment.

In Week 9, you completed your Part 1 for this Assignment. For this week, you will complete Part 2 where you will create a research question that can be answered through multiple regression using dummy variables.

Part 2

To prepare for this Part 2 of your Assignment:

  • Review Warner's Chapter 12 and Chapter 2 of the Wagner course text and the media program found in this week's Learning Resources and consider the use of dummy variables.
  • Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in this week's Learning Resources.
  • Consider the following:
  • Create a research question with metric variables and one variable that requires dummy coding. Estimate the model and report results. Note: You are expected to perform regression diagnostics and report that as well.
  • Once you perform your analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Part 2 Assignment:

Write a 2- to 3-page analysis of your multiple regression using dummy variables results for each research question. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.

Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

Below is Part 1 of this assignment

This assignment is to formulate analysis from a dataset using multiple regression analysis. I chose to use the "High School Longitudinal Study 2009 Dataset." "Multiple Regression is a model that examines the effect of one independent variable on the value of a dependent variable (Frankfort & Leon, 2018, p. 326)." I will investigate the scale of "Student's Mathematics Self Efficacy" which is the dependent variable. The "Student's Mathematics Self Efficacy" can be predicted by "Parents Highest Level of Education" and "Years Math Teachers Has Taught High School Math" and which both are independent variables. The research question for this investigation is, "Whether or not "student's mathematics self-efficacy" can be foreseen by the "parents highest level of education" and "years math teachers has taught high school math".

           Below are the tables formulated to present statistical data and to check effect of an independent variables on the value of dependent variable. First is the descriptive data for each variable in this study. The second table shows the correlation between the variables. Under the Pearson Correlation, the correlation between the "scale of student's mathematics self-efficacy" and "parents highest level of education" is .135. The correlation between "scale of student's mathematics self-efficacy" and "years math teacher has taught high school math" is .015. Under the model summary, the "R" value is .135 which is a weak level of prediction. The results of this study showed "parents highest level of education" and "years math teachers has taught high school math" cannot predict the "student's mathematics self-efficacy".

Reference Page

Frankfort-Nachmias, C., & Leon_Guerrero, A. (2018). Social statistics for a diverse society (8th   

          ed.). Thousand Oaks, CA: Saga Publications.

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