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

Answer:

a. The estimated coefficient for size is approximately $s =13.8096595404$

b The number of  predictors are 2

Step-by-step 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