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Veritas-Collective

Group Name: Veritas Collective

Team Members: Franklyn De La Cruz, JJ Krehbiel, Maria Valdes, Mihee Park, Shae Stringer-Jones, Tristan Nguyen

Happiness Indicators

The purpose of this document is to illustrate our intent to move forward with a project centered around the World Happiness Report. Nations across the globe measure productivity and success in many ways. The United States typically uses Gross Domestic Product (GDP) to measure yearly growth and production. Gross domestic product is a monetary measure of the market value of all the final goods and services produced in a specific time period. The higher the GDP, the higher the perception of success. Another indicator of success is the GINI Index. It measures the extent to which the distribution of income among individuals or households, within an economy, deviates from a perfectly equal distribution. The lower on the GINI Index, the more evenly income is distributed. These indices, and others, help us to compare nations across the globe. The measure we will be focusing on is the Happiness Index. The World Happiness Report is a publication of the United Nations. It contains articles and rankings of national happiness, which the report also correlates with various life factors. Looking at indicators other than financial success allows countries to foster a culture focused on different priorities. Through this analysis we plan to find what the most prevalent of these indicators are and if this holistic view gives a better measure of success. We will be using several visual presentation strategies to display answers to the following questions.

Research questions to answer:

  1. Is GDP or GINI a better indicator of happiness?
  2. Which indicator has the highest correlation with happiness?
  3. Do countries with higher happiness scores live longer?
  • Look at a country that has dropped drastically and analyze contributing factors Rough breakdown of tasks: • Collect Datasets • Create Jupyter Notebook and clean data • Format and analyze data • Create visualizations using Pandas and Matplotlib • Summarize findings and prepare presentation

We plan to use the following resources and datasets: https://www.kaggle.com/moradnejad/world-happiness-report-2015-2020

https://data.worldbank.org/indicator/SI.POV.GINI

https://datahub.io/world-bank/si.pov.gini

We reserve the right to edit this list, as we see fit, throughout the project.