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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 model yielded the following results. 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 = 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 model yielded the following results.   = 24   = 124   = 42   = 338   = 196 Calculate the standard error. A) 1.75 B) 4 C) 2 D) 1.72 = 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 model yielded the following results.   = 24   = 124   = 42   = 338   = 196 Calculate the standard error. A) 1.75 B) 4 C) 2 D) 1.72 = 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 model yielded the following results.   = 24   = 124   = 42   = 338   = 196 Calculate the standard error. A) 1.75 B) 4 C) 2 D) 1.72 = 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 model yielded the following results.   = 24   = 124   = 42   = 338   = 196 Calculate the standard error. A) 1.75 B) 4 C) 2 D) 1.72 = 196 Calculate the standard error.

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