Black Friday deal

Linear Regression Analysis of US Census Data

Banner Image


The goal is to predict a person's income based on their age, gender, class of worker, and education level. We validated a model using numerical representation, in particular R squared and RMSE. PINCP, AGEP, SEX, SCHL data are selected within the PUMS dataset. The beta coefficient for age is 0.012 which means that for every addition increase in age we estimate that the salary increases by a factor of 10^0.012 = 1.028. The beta coefficient for bachelor’s degree is 0.39 which means that people with bachelor’s degree make 10^0.39 = 2.45 times as much as those who did not completed high school. 

Are you a contestant for RMDS 2021 Data Science Competition?
Type: Other
Release Date: Aug 19, 2019
Last Updated: Nov 29, 2019

Average rating is 4.4 with 5 vote(s)


Please sign in or create an account to give a rating or comment.

Please sign in or create an account to view the download file