I worked with an exponential distribution before at work. At first, it seemed like we could model them like gaussian because the part of the data we were intere

I worked with an exponential distribution before at work. At first, it seemed like we could model them like gaussian because the part of the data we were interested in was "close enough" to a gaussian. We already wrote code that worked for our other data that was gaussian. As it turns out, I was wrong. The thing that can't be easily seen in pictures is that exponential distributions move differently than gaussian distributions. When the variance increases for a gaussian, it flattens out. When the variance increases for an exponential, the whole thing spikes out to the right, and the area under the tail actually increases. It really screwed things up until I started treating it for what it really was.