A literature review of some statistical method in the style of a TREE (Trends in Ecology and Evolution) paper. The review should be critical not just descriptive. That is, enter the debate. Is post hoc power analysis a useful tool or not? When should we use least squares and when should we use a reduced major axis regression? Should we ever analyze ratios? Why do so many people use principal components analysis to measure differences between groups? How do we compare body size-correlated measures (egg size for example) among populations if these populations differ in body size? Are resampling methods always better than parametric methods? Should we abandon the Bonferroni world-view? Should we even bother with frequentist (P-value) statistics?
If you want to do something original, pour through recent issues of some journal in some field and count how people misinterpret p-values (e.g. "these two groups are really different (P=0.000000000000001)"). Or, how often do people use a Model I regression when they should have used model II. Or, how often could people have used a directional test but didn't? Or, how many people use PCA when they should have used DFA? I would love to a paper that included this sort of original [library] data!
Please e-mail me about ideas and I want you to get started by the week after break. That is, on 7 March, I want an summary of your paper with at least 5 references. The paper will be due May 9, which is the monday of exam weeks. No length limit. Any fewer than 5 references will almost certainly not be sufficient research on your part.