/Analyzing-World-Happiness-Report-2019

The World Happiness Report measures the overall state of global happiness by factoring in each country's status in economy, health, social support, government trust, etc. and ranks the countries by how happy their citizens perceive themselves to be. Since it covers different factors, it can be a useful guide to measure policy effectiveness and good governance and assess the quality of life among countries. In this project, we explore and visualize the distribution of happiness scores among countries, identify strong determinants and relationship of factors to one another, and apply ML Linear Regression to test the model used for the report. Here is the link to the slide pack used: https://drive.google.com/file/d/15q6585HzYGlcFx3PbSPpw5spmRCw_Ozx/view?usp=sharing Proponents of the project are Janine Cheong, Raymund Norada, Karen Salas, and Maico Rebong. This final project serves as a requirement in our Diploma Course in Foundations in Data Science under DLSU. This study was awarded Best in Data Analysis among the thirteen presentations.

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