OBJECTIVE
To analyze different attributes that influence life expectancy in countries
FINDINGS
The most important attributes across life expectancy are Schooling, Income composition of resources, Adult Mortality and HIV/AIDS.
METHODOLOGY
DATASET: Life Expectancy from Kaggle (Life Expectancy (WHO) | Kaggle)
Linear Regression to find the best variables
Data exploration using SAS
In 2015 the top 5 countries with high life expectancy are Slovenia ( Average 88 of years) , Denmark ( Average of 86 years old), Chile( Average of 85 years old), Cyprus( Average of 85 years old), and Japan ( Average of 83.7 years old)
The average for countries with low life expectancy is between 53 to 51 years old all these countries are on the African continent.
How it was build on SAS?
Linear Regression - Variables that best explain Life Expectancy
Best Model : 0.9562
RMSE - Residual Matrics : -0.1566515
On an avg what is the percentage error I got on every Life Expectancy prediction
train.rmse <- sqrt(mean((trainDf$residual)^2))
test.rmse <- sqrt(mean((testDf$residual)^2))
test.rmse - train.rmse
Homoskadasticity
homoscedasticity means a situation in which the variance of the dependent variable is the same for all the data
CORRELATION ANALISES
Adult Mortality and HIV/AIDS have negative correlation
Income composition of resources and Schooling have positive correlation
MOST SIGNIFICANT VARIABLE ACROSS LIFE EXPECTANCY
Countries that use its income resources productively are more likely to have their citizens live longer
The number of years people spend learning in school could potentially increase their life expectancy
For every 1000 people in a developed country less than 100 people die compared to some countries that have lowest life expectancy rates where more than 600 people die for every 1000.
As the mortality rate increases from HIV/AIDS the life expectancy decreases.
Example of how it was built on SAS
CONCLUSION
• Some countries build a system to prevent the population from dying early while other countries don’t have enough resources to keep people alive in the long term.
•The longer the life expectancy the lower the mortality rate
Comparison countries with high Life Expectancy in 2015 how they were in 2019
Slovenia decreased 7 years
Denmark decreased 5 years
Chile decreased 5 years
Cyprus decreased 4 years
Japan increased 1 year
RECOMMENDATION
My recommendation and my desire is that we can live in a world where everyone is able to have a healthy, long and meaningful life.
Lila Reis
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