# The Importance Of Distributions

2017-11-03

We see that for the entire curve, our odds of success goes down when we add criticals and for most of the curve, it goes up for 3z8. Lets think about why. We know the guards are more likely to roll a 20 and less likely to roll a 1 from the distribution we made earlier. This happens about 14% of the time, which is pretty common, and when it happens, the rogue has to have a very high modifier and still roll well to overcome it unless they also roll a 20. On the other hand, with 3z8 system, criticals are far less common and everyone rolls close to average more of the time. The expected value for the rogue is ~10.5, where as it is ~14 for the guards, so when everyone performs close to average, the rogue only needs a small modifier to have a reasonable chance of success.

It’s a nice spin on a classic statistics lesson.

## Interpreting P-Value Histograms

2017-11-15

David Robinson visualizes and interprets different p-value histograms: So you’re a scientist or data analyst, and you have a little experience interpreting p-values from statistical tests. But then you come across a case where you have hundreds, thousands, or even millions of p-values. Perhaps you ran a statistical test on each gene in an organism, or on […]

## The Magic Of Sampling

2017-11-13

Nathan LeClaire reminds us of an important story that statisticians have been telling us for a couple centuries: It starts slowly. Maybe your home-grown centralized logging cluster becomes more difficult to operate, demanding unholy amounts of engineer time every week. Maybe engineers start to find that making a query about production is a “go get […]