Tools
Tools
Sheehan, Luke (2021) Life Expectancy Project: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.
Preview |
PDF (Bachelor of Science)
Download (2MB) | Preview |
Abstract
In this report I will be discussing my life expectancy project. I will be covering the background and motivation for this project as well as the key insights and findings that I have taken from it. I will also be explaining the technologies, approach, and data sets that I used to complete my project.
This project focuses on the topic of life expectancy and all the data that surrounds it. This project is built around the fact that there are many different factors that affect life expectancy, and some are not as obvious as others. The aim of the project is to use different data mining and data analytics techniques to help answer the question: what are the factors that affect life expectancy and how does life expectancy differ around the world?
To answer this question, I used the KDD data mining methodology to extract information from the data that I have sourced. Through KDD I discovered insights that help uncover factors that contribute to life expectancy. The data analytics techniques used in this project are Random Forests, clustering, linear and multiple regressions.
Through the KDD methodology and through the data analytics techniques listed, I was able to answer the question that I set for myself (i.e., what are the factors that affect life expectancy?) and produce visualisations of my findings. The key findings from my project are:
• From my Linear regressions I determined that GDP per capita and levels of schooling both correlate to life expectancy.
• Ireland countries has a higher life expectancy than the rest of the world and Ireland’s life expectancy is growing at a faster rate as well.
• Through Random Forests I discovered that the most important factors for determining life expectancy are: Income composition of resources, HIV rates and schooling levels.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science |
| Divisions: | School of Computing > Bachelor of Science (Honours) in Computing |
| Depositing User: | Clara Chan |
| Date Deposited: | 15 Sep 2021 17:09 |
| Last Modified: | 16 Sep 2021 16:47 |
| URI: | https://norma.ncirl.ie/id/eprint/5039 |
Actions (login required)
 |
View Item |