Investigating the Relationship between Global Health and Global Wealth

This project gives you the opportunity to apply the knowledge that you have acquired in statistics to our Global Society. You are going to investigate the possible relationships and make some decisions that might impact your life based on the outcomes.

A topic that has been extensively reported is the relationship between Global Health and Global Wealth.  Although, anecdotally, wealthier countries are expected to have healthier populations, there is significant variability surrounding that relationship.  Attached are some data for you to use to investigate the relationship for yourself. Within that set you will find 22 randomly selected countries from around the world.  Underneath each country you will find descriptive statistics for a variety of economic and healthcare indicators (see the data dictionary for a description of each variable).  Truthfully, there is not one single factor that explains overall health in a selected location.  In fact, we would expect many different variables to maintain relationships with general health. However, for this assignment, you are to choose the indicator that you believe best explains general health, as measured by life expectancy, for nations around the world. You must choose from the data given to you.  Try to eliminate as much bias as possible. 

1.Investigation Results – Using the given data set, investigate 3 possible relationships using Life Expectancy as the response variable and each of the indicators as possible explanatory variables.  Give all results. **NOTE** you should complete parts a - d THREE separate times (50 points).

a.Construct a scatter diagram of the data that you have chosen. Do these variables appear to have a relationship? You can use an online site to create this graph and calculations. https://www.desmos.com/ is a really good site.

b.Write 2 or 3 sentences describing the relationship or lack of a relationship. You should address the linearity, or lack thereof, for each relationship as well as noting any possible outliers that may be evident in the scatterplot.  Be detailed in your explanations.

c.List all statistics that you found. Explain how you calculated the statistics.

d.Are those statistics significant results? Show us why or why not the statistics are significant.

2.Inferences - Write at least one paragraph for each of the following questions.  In the paragraph, you should explain it as though you are talking to someone that is not in a statistics class. In other words, give details.  A paragraph is 3-5 well developed sentences. (50 points)

a.Now that you have investigated 3 separate relationships, which explanatory variable would you determine as the best predictor for Life Expectancy?  In your description, be sure to state the names of the variables and the statistics you used to determine this relationship as the “best”.  Also, be sure to give the full regression model using appropriate notation. 

b.Inherent to every regression model, there is a “rate of change” factor.  Using this factor, describe the behavior of Life Expectancy as the explanatory variable of your choosing changes.  Why do you think Life Expectancy behaves this way as we change each input value?

c.Discuss the overall fitness of your model to the data set.  Using statistical evidence, would you say that the explanatory variable you chose is reasonably predictive of Life Expectancy?  Why or why not?

d.You may have noticed that the United States was not included as a data point in the data set you were given.  Given below are the descriptive statistics from the United States.

Using the model you created, make a prediction of Life Expectancy for the United States.  Also, calculate the residual value.  What do these measures tell us about health care in the United States?  Be sure to defend your answer using statistical evidence.

e.Summarize your findings.  What is “the lesson” we have learned from your investigations?  How do your findings impact your local community?  The global community?  Be descriptive in your response.