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 11174 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 11175 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 11176 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 11177 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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 Winter '14
 Frequency, Frequency distribution, Histogram, AACSB, Statistical charts and diagrams

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