Using data from 50 workers, a researcher estimates Wages = beta_0 + beta_1 Educa

Question

Using data from 50 workers, a researcher estimates Wages = beta_0 + beta_1 Educations + beta_2 Experience + beta_3 Age + epsilon, where Wage is the hourly wage rate and Educations, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. What is the point estimate for beta_1 1.54 0.38 Interpret this value. As Education increase by 1 unit, Wage is predicated to increase by 0.38 units, holding age and Experience constant. As Education increase by 1 unit, Wage is predicated to increase by 0.38 units. As Education increase by 1 unit, Wage is predicated to increase by 1.54 units, holding age and Experience constant. As Education increase by 1 unit, Wage is predicated to increase by 1.54 units. What is the point estimate for beta_2? 0.38 1.54 Interpret this value. As Experience increases by 1 unit, Wage is predicated to increase by 0.38 units, holding age and Education constant. Same interpretation by using 1.54 or -0.06 What is the sample regression equations? (Negative value should be indicated by a minus sign. Round your answers to 2 decimal places.) What is the predicated value for Age = 27, Educations = 4 and Experience = 2. (Do not round intermediate calculations. Round your answer to 2 decimal places.)

Explanation / Answer

a-1)

It is the coefficient of Education,

1.54 [ANSWER]

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a-2)

As it is positive, then

OPTION C. [ANSWER]

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a-3)

it is the coefficient of experience,

0.38 [NSWER]

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a-4)

It is positive 0.38, so

OPTION A. [ANSWER]

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b)

From the table,

y^ = 7.76 + (1.54)Educ + (0.38)Exp + (-0.06)Age [ANSWER]

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c)

Hence,

y^ = 7.76 + (1.54)*4 + (0.38)*2 + (-0.06)*27 = 13.06 [ANSWER]

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