Hi, I am currently working with some data on RStudio (which i have pasted on here), but I am confused and unable to how to proceed with the given information and find the solution to the following questions:

1.Interpret the coefficient estimates. Note that `factor(SEX)2` is the dummy variable that represents the difference between wages between group 2 and the base group group 1, other things equal (i.e., 2=Female, 1=Male). Also, note that `AGE_12` contains five year ranges, so the coefficient is the change in expected wages for an additional five years of age, other things equal.

What is the impact of either being covered but not unionized or being non-unionized relative to unionized workers? Are they both significant? Does this make sense?

2.Conduct a test of significance for the variable `EDUC`. Show all steps and interpret the results.

Call:

lm(formula = HRLYEARN ~ EDUC + AGE_12 + factor(SEX) + factor(MARSTAT) +

factor(UNION), data = foo)

Residuals:

Min1QMedian3QMax

-40.845-7.894-1.9625.82878.869

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 18.45172 0.28938 63.763 < 2e-16

EDUC 3.45415 0.04157 83.092 < 2e-16

AGE_12 0.61311 0.02584 23.723 < 2e-16

factor(SEX)2 -4.77566 0.11703 -40.809 < 2e-16

factor(MARSTAT)2 -1.56908 0.16584 -9.461 < 2e-16

factor(MARSTAT)3 -3.46673 0.62011 -5.590 2.28e-08

factor(MARSTAT)4 -2.26681 0.34882 -6.498 8.20e-11

factor(MARSTAT)5 -2.01411 0.28192 -7.144 9.19e-13

factor(MARSTAT)6 -4.61922 0.15915 -29.024 < 2e-16

factor(UNION)2 -0.09259 0.40589 -0.228 0.82

factor(UNION)3 -3.36436 0.12565 -26.776 < 2e-16

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Signif. codes:

0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 12.06 on 43887 degrees of freedom

Multiple R-squared:0.2257, Adjusted R-squared:0.2256

F-statistic:1280 on 10 and 43887 DF,p-value: < 2.2e-16