Question

The following information may be used in several questions. The following is Excel output from a fitted linear regression model relating the sale price of a home (Y, in thousands of dollars) to age of the home (X) in years. Intercept Age Coefficients 213.365436 -1.207517218 Standard Error Stat 1.450657792 147.0819 0.029970869 -40.2897 P-value 0 1.2E-278 Lower 95% Upper 95% 210.5209309 216.2099411 -1.26628524 -1.148 749195 Refer to the information above on the regression using age to predict selling price. What is the interpretation of b, in context? Hint: read carefully. For each additional year of age, the estimated mean selling price of a home decreases by about $40.29 thousand. For each additional year of age, the estimated mean selling price of a home decreases by about $1.21 thousand. For each additional year of age, the estimated mean selling price of a home increases by about $213.37 thousand. For each additional year of age, the maximum selling price of a home increases by about $1.21 thousand. When the age of the home is 0, the estimated mean selling price of a home is about $213.37 thousand.

Answer 1

Answer. From the provided output, the regression equation of line can be obtained as: y = 213.365436 – 1.2075172102 Here intercept (a)= 213.365 (app.) and slope (6) = - 1.207 (app.) orba-1. 21 (app.) It can be concluded that for each additional year of age, the estimated mean selling price of a home decreases by about $1.21 thousand Thus, option (ii) is correct.