A real estate agency collects data concerning y = the sales price of a house (in thousands of dollars), and x = the home size (in hundreds of square feet). The data are given in the table below. The MINITAB output from fitting a least squares regression line to the data is on the next page.
Real Estate Sales Price Home Size 180 23 98.1 11 173.1 20 136.5 17 141 15 165.9 21 193.5 24 127.8 13 163.5 19 172.5 25
a) By using the formulas illustrated in Example 13.2 (see page 497) and the data provided, verify that (within rounding) b0 = 48.02 and b1 = 5.700, as shown on the MINITAB output.
b) Interpret the meanings of b0 and b1. Does the interpretation of b0 make practical sense?
c) Write the least squares prediction equation.
d) Use the least squares line to obtain a point estimate of the mean sales price of all houses having 2,000 square feet and a point prediction of the sales price of an individual house having 2,000 square feet.