For each hypothesis testing, state the null and alternative, the test statistic, the critical value, your conclusion and your interpretation. Consider significance level u=0.05. Please also use at least two decimals in your calculations. Demand for Coffee Suppose you are employed by a coffee producer and asked to determine the demand function for it. The company is interested in determinants of coffee demand except for its own price. A group of marketing researchers propose the following specification: C = do + In Y+a, In PT +e Another group of researchers propose the following specification: C = Bo +BY+B,PT + u where Y is the income level of consumers, PT is the price of tea, and the level of coffee consumption. An employee of the company gathered appropriate data and provided following estamation results. SSR= Sum of Squares Residuals. EC-C)' = 263.44 (InC) = 2.58. N=85, (Y-PT) = = 37.4 Model 1: C = 27.52+1.32Y +2.44 PT RP=0.38, SSR=113.44, Cov (B, B.,) = -0.005 Model 2: In C =1.18+ 0.39 In Y + 0.63 In PT R?=0.31, SSR =15.67, Cov (@j)=-0.003 Model 3: e= -2.87-0.86 In Y+1.08 In PT R?=0.23, SSR=9.3, Var(In Y) = 2.99 Model 4: Y = 3.92+2.65 In PT R?=0.12, SSR=28.75, Var(PT) = 10.53 n 10.08 0.23 0.41 0.15 0.14 0.12 1.74 0.61 0.46 15 06 For each hypothesis testing, state the null and alternative, the test statistic, the critical value, your conclusion and your interpretation. Consider significance level u=0.05. Please also use at least two decimals in your calculations. Demand for Coffee Suppose you are employed by a coffee producer and asked to determine the demand function for it. The company is interested in determinants of coffee demand except for its own price. A group of marketing researchers propose the following specification: C = do + In Y+a, In PT +e Another group of researchers propose the following specification: C = Bo +BY+B,PT + u where Y is the income level of consumers, PT is the price of tea, and the level of coffee consumption. An employee of the company gathered appropriate data and provided following estamation results. SSR= Sum of Squares Residuals. EC-C)' = 263.44 (InC) = 2.58. N=85, (Y-PT) = = 37.4 Model 1: C = 27.52+1.32Y +2.44 PT RP=0.38, SSR=113.44, Cov (B, B.,) = -0.005 Model 2: In C =1.18+ 0.39 In Y + 0.63 In PT R?=0.31, SSR =15.67, Cov (@j)=-0.003 Model 3: e= -2.87-0.86 In Y+1.08 In PT R?=0.23, SSR=9.3, Var(In Y) = 2.99 Model 4: Y = 3.92+2.65 In PT R?=0.12, SSR=28.75, Var(PT) = 10.53 n 10.08 0.23 0.41 0.15 0.14 0.12 1.74 0.61 0.46 15 06