Wage

From ISLR v1.2 by Trevor Hastie

Mid-Atlantic Wage Data

Wage and other data for a group of 3000 male workers in the Mid-Atlantic region.

Keywords: datasets

Usage

Wage

Format

A data frame with 3000 observations on the following 11 variables.

year: Year that wage information was recorded
age: Age of worker
maritl: A factor with levels 1. Never Married 2. Married 3. Widowed 4. Divorced and 5. Separated indicating marital status
race: A factor with levels 1. White 2. Black 3. Asian and 4. Other indicating race
education: A factor with levels 1. < HS Grad 2. HS Grad 3. Some College 4. College Grad and 5. Advanced Degree indicating education level
region: Region of the country (mid-atlantic only)
jobclass: A factor with levels 1. Industrial and 2. Information indicating type of job
health: A factor with levels 1. <=Good and 2. >=Very Good indicating health level of worker
health_ins: A factor with levels 1. Yes and 2. No indicating whether worker has health insurance
logwage: Log of workers wage
wage: Workers raw wage

References

James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) An Introduction to Statistical Learning with applications in R, www.StatLearning.com, Springer-Verlag, New York

Examples

# NOT RUN {
summary(Wage)
lm(wage~year+age,data=Wage)
## maybe str(Wage) ; plot(Wage) ...
# }

Documentation reproduced from package ISLR, version 1.2, License: GPL-2

Community examples

akil_elkamel@yahoo.fr at Sep 18, 2017 ISLR v1.1

# Take a look at the Wage dataset, using dim(), str() and summary(). dim(Wage) str(Wage) summary(Wage) # Fit a linear regression model that explains the wage according to the age. Use the lm() function such that wage is a function of age. lm_wage <- lm(wage ~ age, data = Wage) # Define a data.frame for new and unseen samples new <- data.frame(age = c(40, 60, 70)) # Predict the wage for a 40, 60 and 70-year old workers wage_pred <- predict(lm_wage, new) # Plot old data and predictions plot(Wage$wage ~ Wage$age) points(c(40, 60, 70), wage_pred, col = "red", pch=20, cex=2)