(All assignments need to be turned at midnight of the specified date)
Data Prep: Make sure you have 2-3 related X (macroeconomic) variables. Remember that these variables will be quarterly as your Y (Revenue) variable. All variables should be from the same time period. Recall that the first column is dates and second column is your Y (Revenue) variable. Your third column will be X1 (the first macro variable), 4th will be X2 (the second macro variable) and so forth. Label your X variables properly so I can understand what those variables are.
- Create a correlation matrix with p-values (you can find it under Stat>Basic Statistics>Correlation) of Y and all Xs. Explain which relationships are statistically significant, positive or negative? You need to tell me which Xs are more related to Y and which Xs are not. Also check the correlation among the X variables. Write a paragraph about possible negative or positive relation between each X with Y and the X variables among themselves based on the direction of the relationships and the statistical significance based on the p-value. (Hint: Also think about independent Xs assumption violation, do you see any possible signs of multicollinearity?)
- Use scatter plots to confirm the positive or negative relationships you diagnosed in part 1. (Hint: Also, think about linearity assumption violation, do you see any nonlinear relations?)
- Run your first regression and have MINITAB report the VIF and DW test statistic (Stats>Regression>Regression. You can find VIF and DW under options.) Explain your output. Your explanation should include the following paragraphs.
- Interpret regression equation variable by variable. Does the regression equation make sense to you?
- Which variables are statistically significant? Which are not? You can use t-test or p-values.
- Which variables are highly correlated?
- Do you have a “sign switch”?
- Do you have outliers? Are you planning to do anything about them?
- Do you have a good overall model? Use both the r-squared and F-test explanations.
