Understanding the Data:
All report and chart data is presented in quartiles: values that divide a list of numbers into quarters. This type of percentile distribution is a method of both illuminating variation and as well as showing the relative position of any given urgent care center within the distribution. This is a far better approach than using averages as the means of measuring comparisons since averages blur variation.
The 25th Percentile/First Quartile = 25% of the data points falls below this percentile.
The 50th Percentile/Median = 50% of data points are lower and 50% are higher (referred to as "the median"). For example, if a center has a simple series of numbers like: 1,5,10,15,30, the median is 10 (the average would be 12.2 and is typically higher than the median which is not skewed by a single high or low response).
The 75th Percentile/Third Quartile = 75% of the data points falls below this percentile.
Although average is a commonly-used and well understood statistic, median is also a common descriptor used to express a “middle” value in a set of data. This “middle” value is also known as the central tendency. Median is determined by ranking the data from largest to smallest, and then identifying the middle so that there are an equal number of data values larger and smaller than it is. While the average and median can be the same or nearly the same, they are different if more of the data values are clustered toward one end of their range and/or if there are a few extreme values. In statistical terminology, this is called skewness. In this case, the average can be significantly influenced by the few values, making it not very representative of the majority of the values in the data set. Under these circumstances, median gives a better representation of central tendency than average.