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 ŷ = 3 + 1x. MSE = 4
Using the sums of the squares given above,determine the 90 percent prediction interval for tire sales in a month when the advertising expenditure is $5,000.

Question

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 ŷ = 3 + 1x.  MSE = 4
Using the sums of the squares given above,determine the 90 percent prediction interval for tire sales in a month when the advertising expenditure is $5,000.

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The Answer of 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 ŷ = 3 + 1x.  MSE = 4
Using the sums of the squares given above,determine the 90 percent prediction interval for tire sales in a month when the advertising expenditure is $5,000.

A Local Tire Dealer Wants to Predict the Number of Tires