## Articles with the normal distribution tag

A common way of illustrating the idea behind statistical power in null hypothesis significance testing, is by plotting the sampling distributions of the null hypothesis and the alternative hypothesis. Typically, these illustrations highlight the regions that correspond to making a type II error, type I error and correctly rejecting the null hypothesis (i.e. the test’s power). In this post I will show how to create such “power plots” using both ggplot and R’s base graphics.

Read more
In this short post I take a look at how to use R and ggplot2 to visualize effect sizes (Cohen’s d) and how to shade the overlapping area of two distributions.

Read more