{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

# 420Hw04ans - STAT 420 Homework#4 Fall 2007 2.2 The dataset...

This preview shows pages 1–3. Sign up to view the full content.

STAT 420 Fall 2007 Homework #4 2.2 The dataset uswages is drawn as a sample from the Current Population Survey in 1988. Fit a model with weekly wages as the response and years of education and experience as predictors. Report and give a simple interpretation to the regression coefficient for years of education. Now fit the same model but with logged weekly wages. Give an interpretation to the regression coefficient for years of education. Which interpretation is more natural? > library(faraway) > data(uswages) > uswages[1:5,] # to see what the data set looks like wage educ exper race smsa ne mw so we pt 6085 771.60 18 18 0 1 1 0 0 0 0 23701 617.28 15 20 0 1 0 0 0 1 0 16208 957.83 16 9 0 1 0 0 1 0 0 2720 617.28 12 24 0 1 1 0 0 0 0 9723 902.18 14 12 0 1 0 1 0 0 0 > attach(uswages) > > fit1 = lm(wage ~ educ + exper) > summary(fit1) Call: lm(formula = wage ~ educ + exper) Residuals: Min 1Q Median 3Q Max -1018.23 -237.86 -50.87 149.88 7228.61 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -242.7994 50.6816 -4.791 1.78e-06 *** educ 51.1753 3.3419 15.313 < 2e-16 *** exper 9.7748 0.7506 13.023 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 427.9 on 1997 degrees of freedom Multiple R-Squared: 0.1351, Adjusted R-squared: 0.1343 F-statistic: 156 on 2 and 1997 DF, p-value: < 2.2e-16

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
The fitted regression function is wage = – 242.7994 + 51.1753 * educ + 9.7748 * exper. The regression coefficient for years of education is 51.1753. We would expect weekly wages to increase by 51.1753 on average for every 1-year increase of years of education with experience fixed.
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern