The objective of this work is to carry out an exploratory analysis to identify the factors correlated to the reduction or increase in life expectancy and to identify a mathematical model that can be used to predict life expectancy.
Data: world health agency and the united nations, IBGE data, Our World in Data organization and geolocation API.
The data-set aims to answer the following key questions:
- Does various predicting factors which has been chosen initially really affect the Life expectancy?
- What are the predicting variables actually affecting the life expectancy?
- Should a country having a lower life expectancy value(<65) increase its healthcare expenditure in order to improve its average lifespan?
- How does Infant and Adult mortality rates affect life expectancy?
- Does Life Expectancy has positive or negative correlation with eating habits, lifestyle, exercise, smoking, drinking alcohol etc.
- What is the impact of schooling on the lifespan of humans?
- Does Life Expectancy have positive or negative relationship with drinking alcohol?
- Do densely populated countries tend to have lower life expectancy?
- What is the impact of Immunization coverage on life Expectancy?
