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A Local Tire Dealer Wants to Predict the Number of Tires

Question 5

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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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 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 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A) (3.32 12.68) B) (3.74 12.26) C) (6.62 9.38) D) (6.08 9.92) = 196 MSE = 4
Using the sums of the squares given above,determine the 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000.


A) (3.32 12.68)
B) (3.74 12.26)
C) (6.62 9.38)
D) (6.08 9.92)

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