University Report: Analysis of Life Expectancy Determinants (MMA3)

This report presents a statistical analysis of the determinants of life expectancy across 184 countries in 2015. The study investigates the correlation and causation between life expectancy and two key variables: per capita income and the number of children per woman. The methodology involves the use of scatterplots and regression analysis to quantify the relationships. The results indicate a positive correlation between per capita income and life expectancy, whereas the relationship between the number of children per woman and life expectancy is weak. The regression analysis, with an R-squared value of 0.095, suggests that both variables together explain a small portion of the variation in life expectancy. The report concludes that per capita income is a more significant determinant of life expectancy than the number of children per woman, emphasizing the importance of economic factors in influencing global health outcomes.