largely based on the guidelines published here

1) Use meaningful, specific subject headers: The subject header is your golden opportunity to attract qualified experts' attention in around 50 characters or fewer. Don't waste it on babble like “Please help me”; use the space for a super-concise problem description instead.

2) Be precise and informative about your problem: Describe the research you did to try and understand the problem before you asked the question. Describe the steps you took to try and pin down the problem yourself before you asked the question.

3) Describe the goal, not the step: If you are trying to find out how to do something, begin by describing the goal. Only then describe the particular step towards it that you are blocked on.

4) When relevant, paste the R code you've been using, any error message, and possibly the data. It's great to make the problem reproducible by others, especially if it's about an error you're getting. For example, saying "I get an error when I try to run a Tukey test" is hard to help with, but adding the following makes it much easier:

> TukeyHSD(aov(lm(x~tr)))
Error in TukeyHSD.aov(aov(lm(x ~ tr))) : no factors in the fitted model
In addition: Warning message:
In replications(paste("~", xx), data = mf) : non-factors ignored: tr