In a regression of wages on an intercept and two explanatory variables denoting

Question

In a regression of wages on an intercept and two explanatory variables denoting education (educ) and experience (exp), the following coefficient estimates were obtained.

Coefficient estimate p-value for statistical significance

beduc   0.7 0.04

bexp 0.2 0.120

a. Interpret the results above [be precise and to the point; you need (at the most) 2 sentences per coefficient].

b. Given your response above, provide 2 numerical values [no writing here] --

1 statistical value for the impact of education on wages --

1 statistical value for the impact of experience on wages

Explanation / Answer

a) Here, we can see that the predictor variables of education(educ) are significant because their p-values are 0.04.(which is less than common alpha level 0.05). Regression coefficients of education represent the 0.7 mean change in the response variable education for one unit of change in the predictor variable wages while holding other predictors in the model constant

However, the p-value for Experience (0.120) is greater than the common alpha level of 0.05, which indicates that it is not statistically significant. Regression coefficients experience represent the 0 2 mean change in the response variable for one unit of change in the predictor variable wages while holding other predictors in the model constant

b) 1) statistical value for the impact of education on wages is 0.7.

And statistical value for the impact of experience on wages is 0.2.

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