For week 4 we were to work on life expectancy insight analysis of a particular country. My team decided to work on South Africa.

Data were gotten from Kaggle which the original file was actually from WHO containing data from 193 countries between the year 2000 and 2015. We then extracted the data for South Africa.

Data was cleaned and correlation analysis was done to establish a relationship between life expectancy and predicting variables which can be grouped into several broad categories:​Immunization related factors, Mortality factors, Economical factors and Social factors. And we were meant to answer the following questions; Work on a Life Expectancy Insight Analysis on a selected country. Your analysis should answer the following questions. °Do various predicting factors which has been chosen initially really affect Life expectancy? What are the predicting variables actually affecting life expectancy? °Should a country having a lower life expectancy value(<65) increase its healthcare expenditure in order to improve its average lifespan? °How do Infant and Adult mortality rates affect life expectancy? °Does Life Expectancy have a 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 a positive or negative relationship with drinking alcohol? °Do densely populated countries tend to have a lower life expectancy? °What is the impact of Immunization coverage on Life Expectancy?

Insight

From our analysis, we could say the predicting factor selected have an impact on Life expectancy some more than others. Our analysis showed that population, total expenditure and GDP have a positive relationship to Life Expectancy in that as they increase Life expectancy also increases while HIV/AIDS, Under-five deaths, Infant Death, Hepatitis B, Thinness, Adult mortality, Alcohol and Diphtheria have a negative relationship to Life expectancy in that as they increase Life expectancy decreases. Schooling, Measles and BMI which are closer to 0 show that they have little or no effect on Life expectancy. It is advised that countries having a low Life expectancy should increase their health care expenditure which would provide better immunization coverage, better health care facilities and enough health care personnel thereby curbing infant, under-five and adult mortality from illness and diseases.