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 hundreds of tires) and advertising
expenditures (in thousands of dollars). Based on the data set with 20
observations, the simple linear regression model yielded the following results.
(X is advertising expenditure in thousand dollars and Y is tires sold in
hundreds): ?X = 50; ?Y = 100; ?X² = 225; ?Y² = 720; ?XY =
390
Find the Intercept and slope and Write the Regression Equation. Also predict
the amount of tires (in thousand tires) sold when money invested in advertising
is $3500. Calculate the correlation coefficient and coefficient of
determination. Check whether there is a relation between correlation
coefficient and coefficient of determination. Calculate SSE and MSE, and
standard error and t-score of the slope coefficient and comment on the
significance of the slope.