Similarly for data analysis questions it's good to
report what's the exact question you're trying to answer.
What are the steps and tools you use to answer it?
And then it's really important to report what you expected to see so
people will know what the output, why it doesn't match what you expected.
And then, what did you see instead?
And it often helps to report a few of the other solutions you've thought about when
asking the question.
That's just so that
people don't immediately jump to an answer you've already tried and it didn't work.
Something to keep in mind is whenever you're doing an email or
post it's really important that you stay friendly and
positive, especially in the forums in a big class like this.
You want to make sure that everybody has a good experience in the class so
let's try to stay friendly and positive and constructive on the forums.
Some bad posts or email characteristics, are that they are very vague.
They don't explain what the versions are.
They don't expect what the questions are.
So, help, I can't fit a linear model isn't very helpful.
A better question will give you the version number of say the software that's
being used, and what the specific problem is like that there's a seg fault with
a large data frame.
And it's even better if you can be more concise about it.
So, if you can tell exactly what the function is, exactly what the software is,
the sparsest amount of information possible, that's the best.
So, it's kind of trying to balance giving as much detail as you can
with balancing that out with making sure that you don't write a huge
pages long post that people can't get through.
So, hopefully that'll help you get answers to your questions as fast as possible.
