Question

A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of size (measured in thousands of square feet) and whether or not there is a fireplace (FP is 0 if there is no fireplace, 1 if there is a fireplace). Part of the regression output is provided below based on a sample of 20 homes. Some of the information has been omitted.

Variable Coefficients Standard Error t-Stat

Intercept 128.93746 2.6205302 49.203

Size 1.2072436 11.439

FP 6.47601954 1.9803612 3.27

a. The estimated coefficient for size is approximately _____.


b. How many predictors (independent variables) were used in the regression?

Answer 1

a. The estimated coefficient for size is approximately 13.81.

b. In the regression, two predictors are used. These two predictors are size and fireplace (FP).

Step-by-step explanation:

a. The estimated coefficient for size is approximately _____.

Estimated coefficient for size = Standard Error of size * t-Stat of size = 1.2072436 * 11.439 = 13.81

Therefore, the estimated coefficient for size is approximately 13.81.

b. How many predictors (independent variables) were used in the regression?

Independent variables can be described as variables that are changed or manipulated in order to measure the effect of their changes on the dependent variable. Independent variables are therefore also called predictors because they employed to predict the dependent variable.

In the regression, two predictors are used. These two predictors are size and fireplace (FP).