Load the Meat20 file and regress Chicken Sales (ChicCon) as a function of Chicken Price (Chicpric), Beef Price (Beefpric), and Income (Dispinc). When you do that create a Residuals/Data table and list Estimate, Residual, ChicCon, Chicpric, Beefpric, and Dispinc for your own use in answering subsequent questions.
1. Extract and specify the regression equation.
2. What is the estimated chicken sales number when the price of chicken is 0.286; the price of beef is .7048; and the income is 2428.1?
Do a correlation matrix containing the 4 variables used in your model.
3. List the 3 correlations in the matrix that indicate the degree of multicollinearity in the model.
4. From those 3 correlations, how much multicollinearity would you say is present in the model (high, moderate, low)
5. What do the tolerance statistics tell you about the degree of multicollinearity in the model? (fatal, high, moderate, low, very low, none)
6. Compute the point price elasticity of demand for the point defined by the estimated chicken sales for the values of independent variables.
7. Using the minimum words necessary describe the point price elasticity found above.
8. Compute the point cross price elasticity of demand for chicken given a change in the price of beef for the values of independent variables .
9. Using the minimum words necessary describe the relationship between chicken and beef revealed by the point cross price elastic found above.