Suppose that a human resources manager uses a linear regression model to predict income levels of their employees using two independent variables, Years of Education and Years of Experience. If the coefficient of Education is 2573, the coefficient of Experience is 373, and the intercept is 24975, what is the predicted income for a person with 16 years of education and 7 years of experience?

• A. 40,000
• B. 100,000
• C. 60,000
• D. 68,754

Answer: (D)

In linear regression, you predict the outcome by taking the intercept and adding each coefficient multiplied by its corresponding variable. So multiply the Education coefficient by years of education, and the Experience coefficient by years of experience, then add the intercept.

Education contribution: 2573 × 16 = 41,168

Experience contribution: 373 × 7 = 2,611

Intercept: 24,975

Total predicted income = 41,168 + 2,611 + 24,975 = 68,754

So the predicted income is 68,754. This also reflects that each additional year of education adds 2,573 to the predicted income, and each additional year of experience adds 373, holding the other variable constant.