Statistics
- Notes from The Statistical Sleuth book
p-value
I agree that you should never compare p-values directly. The p-value is a strange nonlinear transformation of data that is only interpretable under the null hypothesis. Once you abandon the null (as we do when we observe something with a very low p-value), the p-value itself becomes irrelevant. To put it another way, the p-value is a measure of evidence, it is not an estimate of effect size (as it is often treated, with the idea that a p=.001 effect is larger than a p=.01 effect, etc). Even conditional on sample size, the p-value is not a measure of effect size. The p-value is not . . . « Statistical Modeling, Causal Inference, and Social Science [http://andrewgelman.com/]
Potentially useful links
- Statistics; by Freedman, Pisani, Purves, and Adhikari. Norton publishers.
- Introductory Statistics with R; by Dalgaard. Springer publishers.
- Statistical Computing: An Introduction to Data Analysis using S-Plus; by Crawley. Wiley publishers.
- Statistical Process Control; by Grant, Leavenworth. McGraw-Hill publishers.
- Statistical Methods for the Social Sciences; by Agresti, Finlay. Prentice-Hall publishers.
- Methods of Social Research; by Baily. Free Press publishers.
- Modern Applied Statistics with S-PLUS; by Venables, Ripley. Springer publishers. Zed A. Shaw [http://zedshaw.com/]
