A local tire dealer wants to predict the number of tires sold each month.The dealer believes that the number of tires sold is a linear function of the amount of money invested in advertising.The dealer 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 $\hat { y }$ = 3 + 1x. $\sum X$ = 24 $\sum X ^ { 2 }$ = 124 $\sum Y$ = 42 $\sum Y ^ { 2 }$ = 338 $\sum X Y$ = 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.

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The Answer of A local tire dealer wants to predict the number of tires sold each month.The dealer believes that the number of tires sold is a linear function of the amount of money invested in advertising.The dealer 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 $\hat { y }$ = 3 + 1x. $\sum X$ = 24 $\sum X ^ { 2 }$ = 124 $\sum Y$ = 42 $\sum Y ^ { 2 }$ = 338 $\sum X Y$ = 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 Local Tire Dealer Wants to Predict the Number of Tires