The paper "Life Expectancy at Births " is a great example of a macro and microeconomics case study. Life expectancy at births can be defined as the average number of years that a new child would live given that the current mortality patterns are kept constant. Life expectancy is basically a qualitative reflection of a country’ s quality of life because individuals have the potential of living longer and fuller lives. Thus, life expectancy is an estimation of an individual's life span calculated from average ages of all individuals who die in a particular year.
Also, life expectancy takes a further step in measuring the physical wellness of a country’ s citizenry; it supposes measures such as per capita GNP, literacy rates and even educational attainment. The manner in which life expectancy is affected on a national level is important for economic planners. Inasmuch as various factors are essential for living longer, in solitary, they cannot be the only influencing factors. Undoubtedly, the social and economic conditions of a particular country will affect its citizens, their standards of living, decisions, lifestyles and culture. In essence, citizens of wealthier nations have quality access to modern health facilities, technologies, entertainment, leisure and exercise, and meticulously maintained water and sanitation systems.
It is expected that their life expectancies should naturally be higher than those of struggling economies. However, this is not always true as the analysis will show. It behoves researcher then to investigate the particular social and economic factors that contribute most in determining life expectancy at birth. In this study, the average life expectancy at birth is chosen, because individuals who have lived on past childhood are more likely to enjoy an extended life span compared to the average member of their birth cohort, an approach that easily presents a selection bias.
Thus, this study selected economic and social variables that are comprehensive over across varied social and economic conditions from over 62 countries, hoping that the selected variables would cover more important facets and thus assist in the building of an accurate model of life expectancy. This research uses data to examine how Life Expectancy differs between groups of countries by economy type (industrialised and oil-producing).
The research also examines the relationship between Life expectancy and other variables in the data set other than economy type. In addition, the study also examines the extent to which Life Expectancy can be predicted using the variables other than economy type. Measures used in the study The following methods are appropriately used in the analysis: Comparisons of variable distributions (using the mean, median, standard deviation, skew etc. ) with appropriate comments on what your findings show and how these findings relate to the report aims Basic probability calculated from the data, with appropriate explanations of how calculated in the appendix, and what the probability values found imply in relation to the aims Confidence intervals and appropriate explanations of why they are being used and what they show in relation to the aims. T-test hypothesis test of means or proportions with appropriate explanations of why the tests have been used and what the tests show in relation to the aims Chi-squared tests with appropriate explanations of why the tests are being used and what the results show in relation to the aims Correlation with appropriate explanations of why the techniques are being used and what the results show in relation to the aims.
It is noted that correlations do not show causal links instead they only show how the causation works both ways. Regression with appropriate explanations of why the techniques are being used and what the results show in relation to the aims.