Skip to content

A Ladder Score Linear Regression, with data from The Gallup World Poll, which explains what and how variables impact the average happiness score of a country.

Notifications You must be signed in to change notification settings

summerolmstead/Happiness-Linear-Regression

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 

Repository files navigation

HappinessLinearRegression

From the Gallup World Poll, I explain how happy a country is by using the ladder score as a metric of happiness. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country. These factors explain why some countries rank higher than others which we explain by a linear regression targetting the ladder score. In this project, I utilize my econometrics knowledge.

Our Final Model's Regression Equation is: Ladder Score = 5.5979 - 0.8802*(Logged GDP per capita) + 1.3845*(Logged GDP per capita^2)+ 0.3155*(Social support) + 0.2845*(Freedom to make life choices)

This was the 8th Model created with the best results all out of all else created. This final robust model had an R-Squared value of 82.8% and an adjusted R-Squared value of 82.1%.

About

A Ladder Score Linear Regression, with data from The Gallup World Poll, which explains what and how variables impact the average happiness score of a country.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published