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A Local Tire Dealer Wants to Predict the Number of Tires

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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 equation of the least squares line is 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 3 + 1x. 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 24 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 124 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 42 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 338 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 equation of the least squares line is   = 3 + 1x.   = 24   = 124   = 42   = 338   = 196 MSE = 4 Using the sums of the squares given above,determine the 95% confidence interval for the slope. A) (1.951 4.049)  B) (-4.552 6.552)  C) (-.0492 2.0492)  D) (0.259 1.741) = 196 MSE = 4
Using the sums of the squares given above,determine the 95% confidence interval for the slope.


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