Having data is only half the battle. How do you know your data actually means something? With some simple Python code, you can quickly check if differences in data are actually significant. In ...

If the P value is less than 5%, reject the null hypothesis; if the P value is .05 or more, don't reject the null hypothesis. Statistics textbooks -- and statisticians for that matter -- focus almost ...

Multiple hypothesis testing is an important part of many high-throughput data analysis workflows. A common objective is to maximize the number of discoveries while controlling the expected fraction of ...