Explore >> Select a destination
|
You are here 
|
errorstatistics.com | ||
| | | | |
fharrell.com
|
|
| | | | | p-values are very often misinterpreted. p-values and null hypothesis significant testing have hurt science. This article attempts to catalog all the ways in which these happen. | |
| | | | |
www.statsblogs.com
|
|
| | | | | [AI summary] The article argues against teaching null hypothesis significance testing (NHST) in statistics courses due to its ineffectiveness, danger, and lack of purpose, advocating instead for estimation and meta-analysis as more informative methods. | |
| | | | |
jaydaigle.net
|
|
| | | | | This is the second-part of a three-part series on hypothesis testing. Today we'll look at the way we do hypothesis testing in practice, and how it tends to fail. Modern researchers use hypothesis testing as a tool to develop knowledge, but it's really a tool for making decisions, and so it encourages us to draw strong conclusions from weak evidence. It also encourages us to view studies that don't reject the null hypothesis as failures, which leads even honest and dedicated researchers to do shoddy resea... | |
| | | | |
ewulczyn.github.io
|
|
| | | Data Scientist @ WMF | ||
