Last weekend, I participated in a half-marathon (a 13.1 mile run for the uninitiated). Sure it tested my health but it’s after effect provided a great statistical inquiry. Analysis of the Parks provides a few lessons.

I. Age is of little matter to runners. My results show that age, while statistically significant, has little impact on the timing of a run. In fact, I show below that increasing age by one year increases the total finish time by less than one minute. That’s very impressive when you consider that this equates to an addition of less than 5 seconds per mile.

a. This is course panel data rather than time-series data. While there is little difference amongst people of different ages in this sample it is unclear that runners in this sample will maintain this pattern as they themselves age.

II. Gender does matter. Men run almost 15 minutes faster than their female counterparts of equal age.

Figure 1 below shows the distribution of finish times, in minutes, of all runners at the September 2009 Parks half.

We can see that the values bunch around 120 minutes. Ten percent of runners finish in 98 minutes or less and fifty percent of runners finish in 122 minutes or less.

The results of a linear regression of the finish time based on these variables are in Table 1 below.

Table 1 shows that both variables are statically significant. I’ve used the age difference from (current age-38), as 38 is the median sample age (this should not impact the size of the coefficient but it makes it easier to understand our baseline who is a 38 year old female). The table shows that men finish about 15 minutes earlier than women of similar age and that aging by one year adds about 40 total seconds to finish time.