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 number of bedrooms (BR). 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
`s =13.8096595404`

b The number of predictors are 2

Explanation:

From the table we can see that

The standard error of size is
`e = 1.2072436`

and the test statistics of size is
`T_s = 11.439`

The estimated coefficient for size is evaluated as

`s=e * T_s`

=>
`s =1.2072436\cdot 11.439`

=>
`s =13.8096595404`

The number of predictors are two and this include size and FP