https://handbook.gradientmetrics.com/products/power-calculations/ Recent content in Power Calculations on Handbook Hugo -- gohugo.io https://handbook.gradientmetrics.com/products/power-calculations/analysis-power/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/power-calculations/analysis-power/ Introduction & the goal Motivating Example A more complicated example Introduction & the goal Statistical power is the probability that, If there is an effect That your model will detect that effect At a given confidence level Typically, power will depend on: The size of the effect (the larger the effect, the easier it is to gain statistical power) The sample size (the larger the sample size, the easier it is to gain statistical power) The amount of “noise” (the more noise, the harder it is to gain statistical power) Motivating Example Let’s take an easy example.