Let's see what percentiles mean. Basically, if you were to sort all of the data in a dataset, a given percentile is the point at which that percent of the data is less than the point you're at.

A common example you see talked about a lot, is income distribution. When we talk about the 99th percentile, or the one-percenters, imagine that you were to take all the incomes of everybody in the country, in this case the United States, and sort them by income. The 99th percentile will be the income amount at which 99% of the rest of the country was making less than that amount. It's a very easy way to comprehend it.

The following graph is an example for income distribution:

The preceding image shows an example of income distribution data. For example, at the 99th percentile we can say that 99% of the data points, which represent people in America, make less than $506,553 a year, and one percent make more than that. Conversely, if you're a one-percenter, you're making more than $506,553 a year. Congratulations! But if you're a more typical median person, the 50th percentile defines the point at which half of the people are making less and half are making more than you are, which is the definition of median. The 50th percentile is the same thing as median, and that would be at $42,327 given this dataset. So, if you're making $42,327 a year in the US, you are making exactly the median amount of income for the country.

You can see the problem of income distribution in the graph above. Things tend to be very concentrated toward the high end of the graph, which is a very big political problem right now in the country. We'll see what happens with that, but that's beyond the scope of this book. That's percentiles in a nutshell.