I am confused about these questions. Thanks in advance.
Suppose that you estimate a model of car prices to estimate the value of various charcteristics, The model looks at the price of cari in thousands of dollars (PRICE) as a function of the wamber of doors (DOORS), the age of the car in years (AGS), the number of accidents reported for cari (ACC), the amount of trunk space in square feet (TRUNK), and how long it takes for car to get from 0 miles per hour to 60 miles per hour in seconds (SPEED.). We have 10,000 observations. For hypothesis tests use the standard normal distribution The regression model you want to estimate is: PRICE - +8DOORS + BAGE+8,ACC+8,7RUNK,+ASPEED. + The equation we estimated is below. Standard errors are in parentheses PRICE - 80+ 3.5DOORS, - 18/08 -5.0/CC + Z.OTRUNK - 15SPEED (1) (500 (20) (3 1181 0611 1. You expect the variables AGE, ACC, and SPEED to have negative coefficients, so you want to reject the idea that they have positive coefficients. Create a separate test for each variable to evaluate your expectations at the 10% level. What do you conclude about the relationship of AGI, ACC, and SPEED with PRICEY it. You expect DOORS to have a positive coefficient, so you want to reject the idea that it has a negative coefficient. Create and test the hypotheses to evaluate this at the 1% level. What do you conclude about the relationship of DOORS with PRICEY ill. You expect TRUNK to have a coefficient different than zero, so you want to reject the idea that it is zero. Create and test the hypotheses to evaluate this at the 5% level What do you conclude about the relationship of TRUNK with PRICE? 2 iv. Compate and interpret the p-value of part (iii). Interpret your result. v. What would happen to the power of the test in partii, (1-B), if the sample size increased? Suppose that you estimate a model of car prices to estimate the value of various charcteristics, The model looks at the price of cari in thousands of dollars (PRICE) as a function of the wamber of doors (DOORS), the age of the car in years (AGS), the number of accidents reported for cari (ACC), the amount of trunk space in square feet (TRUNK), and how long it takes for car to get from 0 miles per hour to 60 miles per hour in seconds (SPEED.). We have 10,000 observations. For hypothesis tests use the standard normal distribution The regression model you want to estimate is: PRICE - +8DOORS + BAGE+8,ACC+8,7RUNK,+ASPEED. + The equation we estimated is below. Standard errors are in parentheses PRICE - 80+ 3.5DOORS, - 18/08 -5.0/CC + Z.OTRUNK - 15SPEED (1) (500 (20) (3 1181 0611 1. You expect the variables AGE, ACC, and SPEED to have negative coefficients, so you want to reject the idea that they have positive coefficients. Create a separate test for each variable to evaluate your expectations at the 10% level. What do you conclude about the relationship of AGI, ACC, and SPEED with PRICEY it. You expect DOORS to have a positive coefficient, so you want to reject the idea that it has a negative coefficient. Create and test the hypotheses to evaluate this at the 1% level. What do you conclude about the relationship of DOORS with PRICEY ill. You expect TRUNK to have a coefficient different than zero, so you want to reject the idea that it is zero. Create and test the hypotheses to evaluate this at the 5% level What do you conclude about the relationship of TRUNK with PRICE? 2 iv. Compate and interpret the p-value of part (iii). Interpret your result. v. What would happen to the power of the test in partii, (1-B), if the sample size increased
