A developer who specializes in summer cottage properties is considering purchasing a large tract of land adjoining a lake. The current owner of the tract has already subdivided the land into separate building lots and has prepared the lots by removing some of the trees. The developer wants to forecast the value of each lot. From previous experience, the developer knows that the most important factors affecting the price (in $1000s) of the lot are size (in thousands sq .ft.), number of mature trees, and distance (in feet) to the lake. From a nearby area, the developer gathers the relevant data for 60 recently sold lots. A multiple linear regression was performed using Excel.

Regression Statistics Multiple R 0.4924 R Square 0.2425 Adjusted R Square 0.2019 Standard Error 40.2435 Observations 60 ANOVA df SS MS F Sig F Regression 3 29029.72 9676.572 5.9749 0.0013 Residual 56 90694.33 1619.542 Total 59 119724 Standard Coefficients Error t Stat P-value Intercept 51.3912 23.5165 2.1853 0.0331 Lot size 0.6999 0.5589 1.2524 0.2156 Trees 0.6788 0.2293 2.9603 0.0045 Distance -0.3784 0.1952 -1.9380 0.0577\f\f