Please help with 3b and 4. I will like.

First question on second page.

Page 2 (10 points total) You've been hired by a regional franchiser of take-and-bake pizza outlets to analyze demand for their pizza. Based on data from fifteen of the company's outlets, you've estimated a demand function of the form: Q = ebo phi Abzyb3@" where Q is quantity demanded (measured in number of pizzas sold per month), P is price (measured in $/pizza), A is advertising expenditure($ per month), Y is disposable income per household ($ per month), and u is a random error term. Taking the natural log of both sides of this expression makes it linear in the parameters, so the parameters can be estimated with linear regression. Your regression results follow: Variable Parameter Standard t - Estimate Error statistic Intercept -13.637 3.230 -4.22 In (P) 0.6702 0.1152 -5.82 In (A ) 1.2944 0.1424 9.09 In (Y) 1.1467 0.3721 3.08 R-Squared: 0.766, Number of Observations: 20 Va) (3 points) It appears demand for pizza is price inelastic. If this is true, will revenue increase or decrease if you increase the price you charge for pizza, holding everything else constant (Explain briefly why you think so)? (b) (7 points) Use a one-tailed test with a 0.05 significance level to determine whether demand for pizza is significantly price inelastic. Be sure to state your null and alternative hypotheses, to show your calculations, and to identify the critical t value. Just need help with this onePage 3 of 3 (9 points total) In your work for the pizza franchiser, you've also estimated a linear demand function. The following is a simplified version of your regression results for the linear demand function: Q = 200 - 2600P + 1.00A + 1.50Y where, once again, Q is quantity demanded (measured in number of pizzas sold per month), P is price (measured in $/pizza), A is advertising expenditure (measured in $/month), and Y is disposable income per household (measured in $/month). Consider a pizza outlet where: P = $15.00 A = $20,000 Y = $33,000 (a) (3 points) Use these regression results to calculate the projected level of pizza demand for this outlet - i.e., the projected level of Q. (Show your calculations.) (b) (3 points) Using your answer to part (a) and other information given above, calculate the point price elasticity of demand for pizza at this outlet. (Show your calculations.) (c) (3 points) Using your answer to part (a) and other information given above, calculate the point income elasticity of demand for pizza at this outlet. (Show your calculations. )