2. Suppose demand for a product is determined by its price, consumers' income, and the price of a related good. Use Q for demand, P for price, M for income, and PR for price of related good. The demand function is estimated using regression analysis. The results are reported below: SUMMARY OUTPUT Regression Statistics Multiple R 0313152135 R Square 0833821042 Adjusted R Square 0.159552505 Standard Error 5302842631 Observations 65 Standard Coefficients Error t Stat Fvalue Intercept 125.56 15.87 P -5.39 3.08 ??? M 0.069 0.046 PR 10.98 2.73 1) What is the Rzof this regression? (5pts) 2) What is the degrees of freedom of this regression? (5pts) 3) What is the effect of a one-dollar increase in price (P) on demand (Q)? (5pts) 4) What is the effect of a onedollar increase in income (M) on demand (Q)? (5pts) 5) What is the effect of a one-dollar increase in price of related good (PR) on demand (Q)? (5pts) 6) Calculate the t Stat (ort ratio marked with \"27??\" in the table) for the coefcient on P? (5ptS) 7) Test whether the effect of P on Q is signicant at the 5% signicance level. Show your work. (5pts) 8) Using the p-value 0.046 in the table, test if the effect of M on Q is signicant at the 5% signicance level. (5pts) 9) Using the values P=100, M=35,000, and PR=40, predict the demand (Q)? (5pts) 10) Using the value of predicted Q you just calculated for part 9), calculate the estimates of The price elasticity of demand. Show your work. (5pts) The income elasticity of demand. Show your work. (5pts) The crossprice elasticity of demand. Show your work. (5pts)