# How to determine the sample distribution based on a survey involving six variables?

This question might be too naive, but I need to understand this point. Suppose I ran a survey for a product for 1000 individuals & collected the data for various aspects of it. Let's say the categories are X1, X2, X3, X4, X5 and X6.

So, now I have 6 variables. I want to know the type of the distribution of the sample.

My question is how to know the distribution of this sample.

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There is no single answer for your question, but you can approximate the six distributions to a varying degree of accuracy. First thing you should do is plot them using either histogram (hist() in R) or a kernel density estimate (density()). It should give you and idea as to what parametric family (exponential, normal, log-normal...) might provide you with a reasonable fit. If there is one, you can proceed with estimating the parameters.

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Thanks Alex! I just want to clarify myself a bit more. According to what you are saying, I've to plot histogram (or any other approach) for each variable & then decide the parametric family of the sample. And presume other variables have the same parametric family.Or I've to plot histogram for each variable individually to get the decide the parametric family for each variable? –  Ari Aug 9 '11 at 11:58
You should do that for each variable, as you do not know for sure that they're equally distributed –  nico Aug 9 '11 at 13:39
Thanks Nico! Things are now much clearer to me. –  Ari Aug 9 '11 at 13:57
@Alex:I'm marking this as the right answer even though StasK also gave a part of the answer, as your answer is closest to what i was looking for.But I wish I can mark both the answers! –  Ari Aug 9 '11 at 18:03