happy3483t583

3 ms·

1. 1.▲
   by happy3483t583 3y ago

   > doesn't have such an easy and commonly accepted "THIS IS SIGNIFICANT AND BY GOLLY I AM RIGHT!" signal. Part of the ongoing stats revolution is abandoning the binary significance test, because it's often misaligned w
2. 2.▲
   by happy3483t583 3y ago

   Gateway drug: Everyone's favorite old-school t-test, brought into the modern world: https://www.sumsar.net/best_online/ Here's the story of the tool: https://jkkweb.sitehost.iu.edu/articles&#x
3. 3.▲
   by happy3483t583 3y ago

   > is (thus) very sensitive to the probability of the prior Standard practice is to test sensitivity of the posterior against various priors. They're often non-informative, e.g., `effectSize ~ N(0, wide)`, and the results are quite
4. 4.▲
   by happy3483t583 3y ago

   It's both. I've consulted in many situations where people make horrible business decisions based on "statistically significant." People mistake p-values for p(hypothesis|data), mistake p-values for effect size ("it&
5. 5.▲
   by happy3483t583 3y ago

   It's good but it's old-school, focusing on traditional null hypothesis significance testing and related ideas. These ideas have been under attack for decades, most recently as being one cause of the scientific replicability proble