The purpose of this assignment is comparing an original hypothesis with a partial result when controlling for a second independent variable. The paper should be written in an essay style and use both the quantitative data (i.e. the regression results) and the existing literature on the topic. This paper is an opportunity to incorporate quantitative data into your research paper and support your argument by quantitative data.
Step 1: Select two variables from the dataset that you want to know about their relationship (make sure both variables are on interval level). The variables must be different from the ones that you used for Assignment II. Create a hypothesis (original hypothesis) on the relationship between the two variables.
Step 2: Conduct a literature review of 5 to 6 scholarly sources about your original hypothesis. The literature should include journal articles, book chapters, published research/census, or research reports.
Step 3: Examine the relationship between the two variables by carrying out a Bivariate Regression. Explain the finding by interpreting the R-square, the Y inception, the Slope, and the Beta of your bivariate output table.
Step 4: Add a second Independent Variable as your control variable (make sure the new independent variable is either interval, correctly coded ordinal, or dichotomous nominal variable). Carry out a Multivariate Regression. Report the results and explain how the control variable affects the original hypothesis. Explain your reasons by interpreting the R-square, the Y inception, the Slope, and the Beta in the Multivariate Regression output table.
Structure: the assignment should be organized in four sections divided by subtitles as follows:
1. Introduction (1-2 pages): introduce the topic, your research question, your original hypothesis and its components (independent, control, and dependent variables), explain the purpose of your research (i.e. testing the original hypothesis by controlling for a second factor). Also explain why you think controlling for a second factor is important in your analysis. Introduce also your methodology (i.e. the literature review and the quantitative method you use for developing the hypothesis). (15%)
2. Literature review and discussions (3-4 pages): read 5 to 6 sources on the original hypothesis and report your finding about the existing knowledge on the issue (30%)
3. Quantitative Research (no page limit): Step 1: carry out a bivariate regression and copy and paste the “Model Summary” and “Coefficients” output tables. Explain what the results tell you about the relationship between the two variables, the strength and direction of the relationship, and its statistical significance. Explain these issues by interpreting the relevant statistics including the R-square, the Y inception, the Slope, the Beta, and the significance). Step 2: Carry out a multivariate regression by adding your second independent variable that you want to control for. Copy and paste the “Model Summary” and “Coefficients” output tables. Explain what the new results tell you about the original hypothesis: how the addition of a third variable affects the original hypothesis? Explain it by comparing the relevant statistics of the two results (i.e. the Adjusted R-square, the Y inception, the Slope, the Beta, and the significance). 40%
4. Conclusion (1-2 pages): Conclude your finding about the original hypothesis and the impact of the control variable on the original relationship. Explain what the comparison of the two results tells you about the importance of multiple regression and controlling for a second factor? Does this finding support or challenge the existing literature on the topic? Outline your main findings from both bivariate and multivariate regression results.
(15%).
