Testing Your Data for Illusions
Here’s a useful way to think about statistical significance. When looking at your data, what’s the probability that it looks like something is there, when in fact nothing is there. Randomness in data (because of sampling) often causes illusions. So testing for significance is all about measuring whether the patterns we see in our data…