Question

A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) as hereunder. A total number of _(i) employees were selected for this study:

EARN_(i) = B₍₀₎ + B₍₁₎ YRSEDUC_(i) + u_(i)

Moreover, by applying this model on a database, the researcher found that the GRETL results shows the "coefficient of determination"= 0.130537 (under 5% level of significance)

Using the above findings, answer the following questions:

A-Comment about the "coefficient of determination" on this model.

B-What is the other name of the coefficient of determination?

C-By looking at this coefficient, what can be concluded about the goodness of fit for the model?

Answer 1

Given that,

Regression equation:

where,

EARN = Salaries of selected employees

YRSEDUC = Years of Education

coefficient of determination = 0.130537

(A) The coefficient of determination of 0.130537 states that the 13 percent of the variation in the salaries of selected employees will be explained by the years of education.

(B) The coefficient of determination is also known as ''R-squared'' which indicates that how much of the variation in the dependent variable is explained by the independent variables.

(C) As the value of R-squared is very less .i.e. 13%, therefore, the model is not fitted well.