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Unformatted text preview: edict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Determine the value of the F statistic. A. 1.75 B. 4.00 C. 8.75 D. 7.00 102. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the estimated slope. A. 1.58 B. 1.00 C. 1.72 D. 2.95 1-1174 Chapter 01 - An Introduction to Business Statistics 103. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Determine the value of the estimated y intercept. A. 1.00 B. 7.00 C. 4.00 D. 3.00 104. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Calculate the standard error. A. 1.75 B. 4 C. 2 D. 1.72 1-1175 Chapter 01 - An Introduction to Business Statistics 105. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at α = .05 and test H0: β1 ≤ 0 vs. Ha: β1 > 0. A. 2.132, reject the null hypothesis B. 2.132, fail to reject the null hypothesis C. 2.645, reject the null hypothesis D. 2.645, fail to reject the null hypothesis 106. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Find the rejection point for the t statistic at α = .05 and test H0: β1 = 0 vs. Ha: β1 ≠ 0. A. 2.776, reject the null hypothesis B. 2.776, fail to reject the null hypothesis C. 2.645, reject the null hypothesis D. 2.645, fail to reject the null hypothesis 1-1176 Chapter 01 - An Introduction to Business Statistics 107. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Calculate the coefficient of determination. A. .7977 B. .6364 C. .3780 D. .1428 108. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression model yielded the following results. = 24 = 124 = 42 = 338 = 196 Calculate the sample correlation coefficient. A. .7977 B. .6364 C. .3780 D. .1428 1-1177 Chapter 01 - An Introduction to Business Statistics 109. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of mo...
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This document was uploaded on 01/20/2014.

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