Descriptive Statistics
Let's say you had an argument with a friend about who is the best tennis player the world has ever seen. You support Roger Federar whereas your friend supports Rafael Nadal. That another friend of yours supports Djokovic is a different story that we will not get into right now.
Both of you can sit down and spend the next couple of years going about every match they played against each other and with the other greats. That is plain simple raw data and it would take an eternity before you reach a conclusion, if at all you do reach one.
But that's not how people debate. You may start with the titles won but quickly get into a comparison on aspects like 1st serve won, break points saved, double faults, and many more.
Here is a comparison of Roger and Rafael on these aspects as per Ultimate Tennis Statistics.
| Statistic | Roger Federer | Rafael Nadal |
| 1st Serve % | 62.1% | 68.3% |
| Break Points Saved % | 67.3% | 66.4% |
| Double Fault % | 2.4% | 2.2% |
These statistics summarize a ton of raw data from hundreds of games these two giants played over the years. Rather than pouring over the entirety of this raw data, we are using these summaries to quickly and simply further our arguments on who is a better player. Such summaries are called Descriptive statistics. They help you get meaning out of the raw data.
However, like with any summary, you lose out on the nuances, and many times the summary gives an inaccurate picture of the underlying data.
Let's explore this and more in the next section.