EDUCATION: EDUCATION data
In profpetrie/regclass: Tools for an Introductory Class in Regression and Modeling

Data on the College GPAs of students in an introductory statistics class

1	data("EDUCATION")

A data frame with 607 observations on the following 18 variables.

CollegeGPA: a numeric vector
Gender: a factor with levels Female Male
HSGPA: a numeric vector, can range up to 5 if the high school allowed it
ACT: a numeric vector, ACT score
APHours: a numeric vector, number of AP hours student took in HS
JobHours: a numeric vector, number of hours student currently works on average
School: a factor with levels Private Public, type of HS
LanguagesSpoken: a numeric vector
HSHonorsClasses: a numeric vector, number of honors classes taken in HS
SmokeInHS: a factor with levels No Yes
PayCollegeNoLoans: a factor with levels No Yes, can the student and his/her family pay for the University of Tennessee without taking out loans?
ClubsInHS: a numeric vector, number of clubs belonged to in HS
JobInHS: a factor with levels No Yes, whether the student maintained a job at some point while in HS
Churchgoer: a factor with levels No Yes, answer to the question Do you regularly attend chruch?
Height: a numeric vector (inches)
Weight: a numeric vector (lbs)
Family: what position they are in the family, a factor with levels Middle Child Oldest Child Only Child Youngest Child
Pet: favorite pet, a factor with levels Both Cat Dog Neither

Responses are from students in an introductory statistics class at the University of Tennessee in 2010. One goal to try to predict someone's college GPA from some of the students' characteristics. What information about a high school student could a college admission's counselor use to anticipate that student's performance in college?

profpetrie/regclass documentation built on May 26, 2019, 8:33 a.m.