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1. Describe the policy issue and outline the broad nature of the quantitative analysis that you will undertake.

2. Describe the ideal data that, if it were available, would allow you to analyze the issue.

3. Describe the data that is actually available and how it maps with the ideal data. Outline the strengths and weaknesses of using the available data to examine the problem.

4. Collect, clean, and format the data for use in Tableau.

5. Use Tableau to present a summary (e.g., average, median, standard deviation, maximum, minimum) of the data in either a table or graphs. Indicate if there is anything noteworthy about the data that might have an impact on the subsequent analysis.

6. Use Tableau to present the data graphically in a way that allows you to examine or explore the policy issue. In particular, use scatter plots to show the relationships that exist between the variables.

7. Usingthegraphsyouhaveprepared,describethekeyvariablesandtherelationshipsthatyou observe between the key variables, as well as the impact or inﬂuence of “third” variables. Please note that this question is one of the more important questions in the assignment and should receive an appropriate amount of attention.

8. Outline at least one regression that you wish to run to further explore the relationships between your variables (you must have at least two explanatory variables in the regression in addition to the intercept). What are the key variables of interest in the regression? What is the expected sign of the coefﬁcient in front of these variables? How did you arrive at a determination of the expected sign?

9. Are there variables missing that you think would be important to include if they were available? What are they and why are they important?

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10. Basedonyourunderstandingofthepolicyissueandyourbeliefsabouttheexpectedsignand magnitudeofthecoefﬁcients,formulateanullhypothesisH0 thatyouwishtotest(H0 should be expressed in terms of the unknown parameters in the regression). What is the connection between the null hypothesis and your policy question? What is the alternative hypothesis Ha? Specify the level of statistical signiﬁcance that you will use.

11. Run the regressions and present the results in a table.

12. Test H0 using the regression results. Indicate whether you reject or do not reject H0.

13. Are there any reasons to expect that your coefﬁcient estimates might be biased in one way or the other? If yes, what are they?

14. Use the results of your graphical and regression analyses to draw conclusions about the policy issue that you are examining.

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