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 the 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. The estimated coefficient for Size is approximately

Variable Coefficients Standard t-Stat

Error

Intercept 13 4.5

Size 2.2 2.1

BR 6.8 2

a. 4.6

b. 1.0

c. 6.6

d. 6.2

Question

Rogelio

Mathematics

11 September, 02:09

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 the 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. The estimated coefficient for Size is approximately

Variable Coefficients Standard t-Stat

Error

Intercept 13 4.5

Size 2.2 2.1

BR 6.8 2

a. 4.6

b. 1.0

c. 6.6

d. 6.2

+2

Answers (1)

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Zion Livingston · Answer 1

estimated coefficient for size = 4.6

Step-by-step explanation:

We have given that

Variable Coefficients Standard Error t-Stat

Intercept 13 4.5

Size 2.2 2.1

BR 6.8 2

The standard error = 2.2

T stat = 2.1

Formula:. t stat = estimated coefficient / standard error

Estimated coefficient = t stat * standard error

Estimated coefficient = 2.1*2.2

=4.62

≈4.6

Thus, estimated coefficient for size = 4.6