Statistics Basics: Mean, Median, Variance

Before you train a single model, you need to understand your data. Not a vague understanding. A precise one. Where do the values cluster? How spread out are they? Are there extreme values pulling everything off? Is the data balanced or skewed heavily to one side? If you skip this step, you build models on data you do not understand. They behave strangely. They perform worse than they should. You cannot debug them because you do not have a clear picture of what went in. Three numbers fix most of