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1. If in a simple linear regression, SST = 315 and the sample correlation coefficient between your dependent and independent variable is 0.96, then the value of SSE is equal to? a. 24.696 b. 290.304 c. 302.4 d. 12.6 e. 0.9216 2. You have randomly selected 100 homes that were sold in New York and run a regression to determine the components that impact the price of a home. You believe the year the house sold (Year - you have coded 1993 to be equal to 1, 1994 to be equal to 2, and so on), distance from Manhattan Central Business District (MCBD), distance from New Jersey (NJ), lot size in square feet (Lot), age of the home (Age), and a dummy variable if the home contains internal heating (Heating=1 if yes). Through the model building process, you did not reject the null hypothesis for the partial F-test. The full and reduced models are presented below: y = 370, 000 + 2, 400 * Year - 2, 000 * MCBD - 1,000 * NJ + 11 * Lot - 700 . Age - 4, 000 * Heating y = 357, 000 - 1,500MCBD + 10 * Lot - 680 * Age - 3,000 * Heating Using the correct model based on the conclusion of the partial F test, what is the estimated selling price of a 1500 square foot lot sold in 1996, 4 miles from Manhattan CBD, 5 miles from NJ, 50 years old, with internal heating and no basement? a. $344,100 b. $348,100 c. $345,370 d. $329,000 e. $360,280 3. Which of the following is not correct regarding the F test for the overall model validity in regression? a. As explained variation increases, we tend to reject the null hypothesis b. Large F statistics result from large explained variation relative to unexplained variation c. As unexplained variation increases, the F test statistic decreases d. The test can be two-tailed on the F distribution depending on the hypothesis e. A higher F statistic is evidence for higher overall signficance of the model