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Statistics Explained

Plain-language explainers of the concepts behind the numbers, so the output of every analysis makes sense.

Both compare groups, but one shows summaries and the other shows shape.

Read every pair's relationship at once, with the significant ones highlighted.

R², VIF, Cook's distance and residual plots — whether to believe the model.

Loadings tell you what a component means; scores tell you where each observation sits.

How SPC tells ordinary variation from a real change — and what the Nelson rules detect.

What correlation does and doesn't mean, and when to use Pearson vs Spearman.

Two measures of center that agree for symmetric data and diverge for skewed data.

Normality, equal variance, independence — what each assumption means and how to check it.

Median, quartiles, the IQR box, whiskers and outliers — read a box plot at a glance.