Mapping the Statistical Significance of Factors Contributing to the World Happiness Report

Charuchith Ranjit,Karan Bhowmick,Department Of Information Technology, Vellore Institute Of Technology, Vellore (Tamil Nadu), India. ,Department Of Computer Science With Specialization In Bioinformatics, Vellore Institute Of Technology, Vellore Tamil Nadu, India.

doi:10.35940/ijeat.f2963.0810621

Abstract

This paper aims to delineate findings of the statistical significance of the factors contributing to the happiness score. The happiness score also termed as ladder score, is a metric used by the United Nations Sustainable Development Solutions Network to metricize the happiness of the citizens in a country. To tackle this issue, we use regression and data visualization. We perform a survey on the factors affecting ladder score and how these factors can be used for predictive analytics. We use Linear Regression, Polynomial Regression, Lasso Regression with cross-validation, and Ridge Regression with cross-validation. Next, we use evaluation metrics like MSE, RMSE, Adjusted r-squared, and r-squared value for the evaluation of the factors on the predictive model. Then, we plot the countries mentioned in the report on a geographical scale based on their happiness index scores. Furthermore, we plot the statistical significance of these factors on a continental scale, to reveal insightful patterns over a larger geographical domain. We aim to bring to light the trends of the aforementioned factors and produce the significance of these results on a world map. The results will help elucidate the global patterns formed by these metrics. An additional application is an extrapolation of the results procured. To augment the metrics of the Word Happiness Report in a statistically comprehensive way. Furthermore, through this evaluation, the world happiness report can be revised to accommodate more inclusive factors and mitigate the redundancy of the factors.

Highlights

The World Happiness Report is a publication of the UN that ranks countries based on happiness, quantified by ratings from citizens in relation to different factors that affect a citizen’s life including economic and social factors
The scoring for the different metrics is done with the help of the Gallup World Poll
This paper correlates job satisfaction and happiness, citing evidence from the World Happiness Report. They plot the job satisfaction in different geographical regions with a “life evaluation” metric This paper clearly describes how to extrapolate the data given by the World Happiness Report for statistical analyses and data visualization.[3]

Summary

Introduction

The World Happiness Report is a publication of the UN that ranks countries based on happiness, quantified by ratings from citizens in relation to different factors that affect a citizen’s life including economic and social factors. The 2021 report had a special emphasis on the effect COVID-19 played. This ranking is done by the Cantril Ladder Survey. The final scores are on a scale of 1 to 10, with 10 being the happiest a citizen can be. The scoring for the different metrics is done with the help of the Gallup World Poll. The Gallup World Poll is a global survey done in the individual countries with more than a hundred questions. There are 6 metrics currently used for getting the ladder score

Objectives

Methods

Findings

Conclusion