Health Insurance Activity

With the costs of medicines and medical treatments growing rapidly, most people need insurance in order to afford the expensive care they may need. In many cases, health insurance covers doctor's visits, hospital stays, prescriptions, and more. Fortunately, many people in the United States have health insurance already. Unfortunately, there are still many people in this country who don't. As of 1997, there were roughly 43 million people living without health insurance. That's around sixteen percent of the entire U.S. population. Often, when people live without health insurance, they don't receive necessary medical care, regular check-ups, or life-saving drugs. This is a large problem in today's society, and a problem that has only recently been addressed with the emergence of Medicare and Medicaid. However, even these programs can't be relied on to insure all Americans. No one specific group or type of people is exempt from having an uninsured population. There are African-Americans who don't have health insurance, just as there are whites and Hispanics. Many women are uninsured, as are many children. Old and young people alike are often living without insurance. It is a problem that effects society as a whole, and although not all groups are affected equally, all have to experience it in some way.

To help solve the problem, researchers can compare the groups and find out which groups need to be targeted the most by health care reformers. In this activity, you will be performing a Chi-Squared test of independence to determine whether there is a relationship between age and insurance coverage.

Using the data set in Excel format. After you have downloaded the data, you will perform a Chi-Squared on it to determine if certain age groups are more likely to be uninsured than others, and thus a target group to start solving the problem. You'll need to use the DIG Stats Online Chi-Squared Calculator; to use it just download the data, open the calculator, and enter the data by hand.

1. What is your null hypothesis?
2. What is your alternate hypothesis?
3. What is the alpha level you're using (the one we typically use at CVGS)?
4. What is the value for degrees of freedom?
5. How is that value calculated?
6. What value does the test return for the Chi-Squared statistic?
7. What value does the test return (from EXCEL using CHISQ.DIST.RT) for the p-value?
8. What does this value indicate related to the null and alternate hypotheses?
9. Is a person's age related to their health insurance?
10. Can a p-value ever actually be zero?
11. Why or why not?

Original work on this document was done by Central Virginia Governor's School students Jordan Israel and Josh Milson-Martula (Class of '00)

Copyright © 2011 Central Virginia Governor's School for Science and Technology, Lynchburg, VA