“Type I” and “Type II” errors, names first given by Jerzy Neyman and Egon Pearson to describe rejecting a null hypothesis when it’s true and accepting one when it’s not, are too vague for stat newcomers (and in general). This is better. [via]
Type I and II errors simplified
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Relationships: The First Time…
When Americans had sex, moved in with someone, and so on. Often not average. Far from normal.
Data Underload #8 – Unsolicited
A few months back, the Caltrans Performance Measurement System (PeMS) …