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 to determine whether there is a relationship between age and insurance coverage.
These data exist in two formats: one is in Excel Data format and one is in
Text 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. (The TI-83 does not have sufficient Chi-Squared computation abilities to be used.)
What are your null and alternate hypotheses? What is the alpha level you're using? What values does the test return for the Chi-Squared and alpha statistics? What about the degrees of freedom? Is a person's age related to their health insurance? How can we use the Chi-Squared and alpha statistics to tell?
Original work on this document was done by Central Virginia Governor's School students Jordan Israel and Josh Milson-Martula (Class of '00)
Copyright © 1999 Central Virginia Governor's School for Science and Technology, Lynchburg, VA