Target time series variable

The variable that we will begin to look at initially will be the variable Not.Covered. We will be interested in examining any possible enrollment trends using this variable. Since the population size will differ depending upon the category, we will calculate the percentage of people not covered in a given year by dividing the raw number corresponding to this variable by the total in the population for that category. This will give us a new variable named Not.Covered.Pct. This will also standardize the metric across the different-sized categories, large and small, and enable us to compare.

After calculating the variable, we can print the first few records, and also print some summary statistics for this one variable:

Note

Note that the average non covered percentage was 14.5% of all of the years, but you can see that there is a considerable able of variation by just looking at the difference between the 1st and 3rd quartile (.15 - .11) = .04. That can translate to...