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GitHub - ASKurz/Doing-Bayesian-Data-Analysis-in-brms-and-the-tidyverse
BRMS kruschke
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bayesian  r.stats  r.bayes 
20 days ago by azadag
Half a dozen frequentist and Bayesian ways to measure the difference in means in two groups | Andrew Heiss
Taking a sample from two groups from a population and seeing if there’s a significant or substantial difference between them is a standard task in statistics. Measuring performance on a test before and after some sort of intervention, measuring average GDP in two different continents, measuring average height in two groups of flowers, etc.—we like to know if any group differences we see are attributable to chance / measurement error, or if they’re real.

Classical frequentist statistics typically measures the difference between groups with a t-test, but t-tests are 100+ years old and statistical methods have advanced a lot since 1908. Nowadays, we can use simulation and/or Bayesian methods to get richer information about the differences between two groups without worrying so much about the assumptions and preconditions for classical t-tests.

Mostly as a resource to future me, here are a bunch of different ways to measure the difference in means in two groups. I’ve done them all in real life projects, but I’m tired of constantly searching my computer for the code to do them:)

These ways can all be adapted to different situations (i.e. difference in proportions, one-sample difference in means, etc.). The process for simulation and Bayesian approaches will be roughly the same, while for frequentist approaches, you’ll need to walk through a statistical test workflow to find the app
frequentist  tests  bayesian  statistics  R 
20 days ago by deprecated

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