Crash Course: Statistics #23 - P-Values, Part 3

We’re going to finish up our discussion of p-values by taking a closer look at how they can get it wrong, and what we can do to minimize those errors.

We’ll discuss Type 1 (when we think we’ve detected an effect, but there actually isn’t one) and Type 2 (when there was an effect we didn’t see) errors and introduce statistical power – which tells us the chance of detecting an effect if there is one.


Data, Graphing & Statistics, Distribution, Probability
High School, College

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