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education/statistics/Hypothesis Tests.md
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@ -60,9 +60,11 @@ Investigators should:
Investigators should not: Investigators should not:
- Blindly compare P to 5% or 1%, there are real world factors that change how important this value is. - Blindly compare P to 5% or 1%, there are real world factors that change how important this value is.
### Data Mining/Snooping/P-hacking
If $n$ tests are made, you can expect that $n * p$ tests are statistically significant (an outlier/unusual result).
Data snooping is **a form of statistical bias manipulating data or analysis to artificially get statistically significant results**.
### Data Mining/Snooping Reliable investigators test their conclusions on an independant batch of data
(Ch 28-29, stat 1040) (Ch 28-29, stat 1040)
## Goodness of fit tests ($\chi ^2$) ## Goodness of fit tests ($\chi ^2$)