A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables
y = sales price (in thousands of dollars)
x1 = total floor area (in square feet)
x2 = number of bedrooms
x3 = distance to nearest high school (in miles)
are used in a multiple regression model. The estimated model is: y = 102 + .079x1 + 23x2 - 7x3
Holding the other variables fixed, what is the average change in sales price for each 100 square foot increase in floor space? In Dollars $
Is this change an increase or a decrease?
The interpretation of the coefficients in the regression model is that the coefficient equals the number of units that the dependent (Y) variable changes for a one unit change in the independent (X) variable. ...
The solution shows how to interpret the given regression coefficients in order to judge whether the situation portrays an increase or decrease. Uses calculations and worded explanation.