Regression analysis
Calculate then explain/interpret the following 14 tasks/tests using the dependent variable (labeled Y)(Sales) and the independent variables (labeled X1 (Calls), X2 (Time), and X3(Years)). Attached is the excel Spreadsheet with the variables.
1. Generate a scatterplot for Y vs X1, including the graph of the "best fit" line. Interpret.
2. Determine the equation of the "best fit" line
3. Determine the coefficient of correlation. Interpret.
4. Determine the coefficient of determination. Interpret.
5. Test the utility of this regression model. Interpret results, including the p-value.
6. Based on items 1-5, analyze the ability of X1 to predict Y
7. Compute a 95% CI for β1 (the population slope). Interpret this interval.
8. Estimate the average for the dependent variable when X1 = 170 using an interval. Interpret.
9. Predict the value of the dependent variable when X1=170 using an interval. Interpret.
10. What can be said about the value of the dependent variable for values of X1 outside the range of the sample values? Explain. Build a model to predict the dependent variable/Y using all of the independent variables/ X1, X2, and X3
11. Prepare a multiple regression model using the designated dependent and 3 independent variables. Explain the equation for this multiple regression model in simple terms.
12. Perform the Global Test for Utility (F-Test). Explain the conclusion.
13. Perform the t-test on each independent variable. Explain the conclusions including your recommendation on which independent variables should be kept and which should be discarded. If any independent variables are to be discarded, re-run the multiple regression, including only the significant independent variables, and summarize your finding on this final model.
14. Is this multiple regression model better than the linear model generated in parts 1-10? Explain.