Answer the following questions: 1. In the simple regression model, the ESS (Expl

Question

Answer the following questions:

1. In the simple regression model, the ESS (Explained Sum of the Squared) summarizes:

A. The variance of the error term

B. The variance of the dependent variable

C. The variance of the residuals

D. The variance of the predicted value of the model

2. Suppose that a researcher using class size (CS) and average test scores (TS) for third grade classes estimates the following simple OLS regression function:

TS = 45.125 - 0.585*CS + u

If a class has 25 students, the regression's prediction for that classroom's average score is:

(do not round and show your work)

Explanation / Answer

(1) Option (D)

ESS describes how well the regression model represents the data used for the modelling purpose. It measures the variance of predicted value of the model.

(2) CS = 25

TS = 45.125 - (0.585 x 25) = 45.125 - 14.625

= 30.500

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