Testing for Multiple Regression.

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User Generated

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wqfnffl

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Mathematics

Course

RSCH 8210

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Part 1

To prepare for this Part 1 of your Assignment:

Review this week’s Learning Resources and media program related to multiple regression.
Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you choose) found in the Learning Resources for this week.
Based on the dataset you chose, construct a research question that can be answered with a multiple regression analysis.
Once you perform your multiple regression analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Part 1 Assignment:

Write a 1- to 2-page analysis of your multiple regression 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.

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.

Tags: Regression

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This week’s Learning Resources include several different ways to identify and assess the issue of missing data in your database. From your assessment and knowledge of possible ways to manipulate data, and to overcome potential challenges presented by the missing data, you will be able to analyze and reach conclusions about your analysis. It is important to recognize when and how to apply the most viable solution to the missing data. In addition, it is important to learn to recognize when your data results could be compromised by missing data.For this, you will analyze the impact of missing data on data analysis.To prepare:Review this week’s Learning Resources.Analysis of missing data. Include the following in your post:An explanation of the importance of handling missing data and skipping patterns and how missing data can affect data analysisA technique on how you may handle missing data appropriately with an explanation of why this technique worksChoose one of the variables you selected for your Scholar-Practitioner Project (select one with missing values) and report proportion of missing for that variableIndicate the possible reason for the missing values in that variable.ReferencesWang, R., Sedransk, J., & Jinn, J. H. (1992). Secondary data analysis when there are missing observations. Journal of the American Statistical Association, 7(420), 952–961. Long, J. A., Bamba, M. I., Ling, B., & Shea, J. A. (2006). Missing race/ethnicity data in Veterans Health Administration based disparities research: A systematic review. Journal of Health Care for the Poor and Underserved, 17(1), 128–140.Langkamp, D. L., Lehman, A., & Lemeshow, S. (2010). Techniques for handling missing data in secondary analyses of large surveys. Academic Pediatrics, 10(3), 205–210.

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