Ten Distributions Worth Knowing
In This Chapter
Delving into distributions that often describe your data
Digging into distributions that arise during statistical significance testing
This chapter describes ten statistical distribution functions you’ll probably encounter in biological research. For each one I provide a graph of what that distribution looks like as well as some useful or interesting facts and formulas.
You find two general types of distributions here:
Distributions that describe random fluctuations in observed data: Your experimental data will often conform to one of the first seven common distributions. These distributions have one or two adjustable parameters that let them “fit” the fluctuations in your observed data.
Common test statistic distributions: The last three distributions — the Student t, chi-square, and Fisher F distributions — don’t describe your observed data; they describe how a test statistic (calculated as part of a statistical significance test) will fluctuate if the null hypothesis is true — that is, if the apparent effects in your ...