This article certainly throws a molotov cocktail into experiemental statistics.
Top 10 ways to save science from its statistical self
Null hypothesis testing should be banished, estimating effect sizes should be emphasized
The article (which is part two in a series) opines on the following:
10. Ban P values
9. Emphasize estimation
8. Rethink confidence intervals
7. Improve meta-analyses
6. Create a Journal of Statistical Shame
5. Better guidelines for scientists and journal editors
4. Require preregistration of study designs
3. Promote better textbooks
2. Alter the incentive structure
1. Rethink media coverage of science
I haven’t read the whole article yet, but their discussion on the null hypothesis and p-values (and the banning thereof by congressional legislation) piqued my interest and thought would be interesting to discuss.
Top 10 ways to save science from its statistical self
Null hypothesis testing should be banished, estimating effect sizes should be emphasized
Statistics is to science as steroids are to baseball. Addictive poison. But at least baseball has attempted to remedy the problem. Science remains mostly in denial.
True, not all uses of statistics in science are evil, just as steroids are sometimes appropriate medicines. But one particular use of statistics — testing null hypotheses — deserves the same fate with science as Pete Rose got with baseball. Banishment.
The article (which is part two in a series) opines on the following:
10. Ban P values
9. Emphasize estimation
8. Rethink confidence intervals
7. Improve meta-analyses
6. Create a Journal of Statistical Shame
5. Better guidelines for scientists and journal editors
4. Require preregistration of study designs
3. Promote better textbooks
2. Alter the incentive structure
1. Rethink media coverage of science
I haven’t read the whole article yet, but their discussion on the null hypothesis and p-values (and the banning thereof by congressional legislation) piqued my interest and thought would be interesting to discuss.