Quote From Hypothesis:
Hi Delta:
It depends on your data; if your data is normally distributed - a Poisson curve - (as most "ideal" data tends to be) then you'll be looking at the following:
student's t-test (two independent variables)
ANOVA (multiple indepedent variables)
Mann Whitney is good if your data is skewed to the left or right (so not normally distributed).
Best thing to do is get some data, plota histogram of it and then find the in-house statistician to give you a hand.
Sorry- but most of this information is incorrect. There are more statistical tests than just 'comparing groups' i.e. ANOVA/Mann-Whitney/T-tests...
The most important thing with getting the right statical test is to check your assumptions. So, ANOVA/t-test's assume that the data form a normal distribution - a bell curve- (not a poisson curve) and that the group standard deviations are equal.
Mann-Whitney U test can be used on non-normal data but still assumes that the group variances are equal and that the distributions between groups look the same.
You may also want to create a model for your data to look at risk factors, or predict outcomes, look at relationships....etc
Anways, I could go on forever explaining the various statistical methods of analysis! If the OP would like to PM me with a description of their data and their hypotheses i.e. what they want to prove/disprove from the data, I can recommend methods of analysis etc.
Billys
P.S. I am a second year PhD student studying statistics, I have an undergrad in stats and do a lot of consultancy work so do know quite a bit about this!