Research Assignment | Get Paper Help

You are required to write a 7–10 page (double-spaced) essay to demonstrate how you apply the statistics that you learn from this course to real-world inquiries in public affairs and administration. You should prepare a quantitative data set for data analysis with at least 50 observations and 5 variables for the essay (at least two variables with interval level measurement and at least one variable with categorical measurement). You should use descriptive statistics to summarize at least two interval level variables and use frequency distribution to summarize one categorical variable. You are also required to use multivariate linear regression and other two inferential analysis techniques you have learned from this course to address meaningful research questions. Your essay should answer the following questions successively:

1) What are your research questions, hypotheses, and observations (analysis units)? Please make sure you specify your dependent variable and independent variables in your hypotheses.
2) Describe the data set you are using: where did you get the data or how were the data collected? How many valid observations in the sample?
3) How is each of the variables in your hypotheses measured? What are the measurement unit and measurement level of each variable? If you recorded any variable or generated any new variable, how did you do that?
4) Use basic descriptive statistics to summarize at least two interval level variables and use frequency distribution to summarize one categorical level variable. You may create a nice table or chart to help you report the data distribution.
5) Which inferential technique (including multivariate linear regression) do you use to test your hypotheses? Why do you think the technique is appropriate? Please make sure you specify your dependent variable and independent variables in your inferential analyses.
6) Report the findings of your inferential analyses and discuss whether each of your hypotheses is supported or not.
7) Discuss implications of your results: How can your results provide suggestions to help improve performance in the field