TLDR
Counts are everywhere, so no matter your background, these data distributions will come in handy. Data distribution tells us what the possible values of a variable are and how often these values occur. The Poisson distribution is usually the starting point when you work with count data. Count data regression with negative binomial distribution is an excellent option if the variance in your data is higher than the mean. In this case, you need another parameter to capture the dispersion of the data. If you expect lot of zeros, try zero-inflated distribution.via the TL;DR App
no story
Written by nikolao | Combines ideas from data science, humanities and social sciences. Views are my own.
