D. Develop a table/s of descriptive statistics for all of the variables you are using in your model. The descriptive statistics should be appropriate to the type of variable. Write a paragraph or two explaining what you see in your descriptive statistics. Bivariate statistics • Calculate the correlations between all of your variables. Put these into a nice table with statistical significance shown. • Run t-tests evaluating whether there are significant differences between all of your variables when NYS = 1 vs when NYS = 0 (you are testing whether the means in New York are different from the rest of the country). Put your results into a nice table with statistical significance shown. • Write a paragraph or two interpreting your correlation and t-test results. How consistent are these findings with your hypotheses so far? E. Regressions • Run a regression for the full national sample with robust standard errors and check the VIF statistic. Export your regression results to a table. • Run two more regressions, one with the subsample of counties from NYS, and one with all the other counties in the US, with robust standard errors. Export both sets of regression results to the same table. • You can decide whether it would be useful to use standardized coefficients and/or semi-partial correlations to aid your interpretation of the data. If you use standardized coefficients please add those results to your table of regression results. • Note all of your regression results should appear together in one table. • Interpret what you see across the regressions. Make sure to compare your full sample results to the subsamples. How does New York compare to the rest of the country? How consistent are these findings with your hypotheses and the existing research? F. Graphics: Think carefully across your findings. What are the most important messages you want to communicate to Dr. Gil-Garcia? Hint: these are likely tied to your hypotheses. Develop 2 to 3 graphics, nicely formatted, to visually demonstrate these key points. At least one of the graphics should visually demonstrate the regression results.
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