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1. Using the cigarette consumption variable as your dependent variable and the cigarette tax variable as your independent variable, do the following: Run a crosstab

1. Using the cigarette consumption variable as your dependent variable and the cigarette tax variable as your independent variable, do the following: Run a crosstab analysis for the two variables a. Since cross tabs are used for ordinal or nominal variables, you will need to convert the DV to an ordinal variable b. To do so, create an ordinal variable (name it cigs3) from the cigarettes variable using the following criteria: i. Minimum-5.50 = 0 ii. 5.51-$9.00 = 1 iii. >9 = 2

3. Interpret the results from the crosstabs. a. Your interpretation should describe the basic pattern (substantive relationship) b. Your interpretation should include a statistical significance test for the relationship i. For crosstabs, you should conduct a Chi-Square test.

4. Run a difference of means test for your DV and IV. a. Recall that a difference of means test requires the IV to be dichotomous b. You should create a new dichotomous measure of cigarette taxes (named cig_tax2) where: i. Minimum-mean = 0 ii. Mean-maximum = 1

5. Interpret the results from the difference of means. a. Your interpretation should discuss the substantive effect (i.e., the difference in means between the two groups) and statistical significance (i.e., was the difference statistically significant). I need to interpret a T-Test (see screencasts for instructions).

6. I need to create a scatterplot for these variables (you should use the continuous versions of eachvariable, not the definite ones). The DV should be on the Y axis, and you should include variable labels for the X and Y axes. The graph also has the correlation coefficient between the two variables.

7. Run a bivariate regression between your DV and IV. (NOTE: Both variables should be continuous)

8. Interpret the results from the regression. Your interpretation should include the following: a. The substantive effect of X on Y (i.e., what does the coefficient tell us) b. Whether the relationship is statistically significant c. The overall goodness of fit for the model (hint: R2)

9. Why do you think the results differed for the analyses?

10. are the results surprising? Why/why not?

The data link is below. Copy and paste the URL; the link will give access to the data needed for this homework assignment.

https://docs.google.com/spreadsheets/d/1--eSvAYAIkQ4dRppiceZ3mUb-NA34rzc/edit?usp=share_link&ouid=106596741055892912212&rtpof=true&sd=true

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