Why do we take normal samples?

Hey everyone!I have a problem on understanding on an intuitively level some things in statistics and therefore I wish that you could help me.My question is about samples.

When we want to make some conclusions about a population we take a sample from the normal distribution. Why do we want our sample to be normal?
Where does this help us?
Why don't we take a sample from other distributions, such as the t-distribution which is similar to the normal?


Fortran must die
Actually we don't take a sample from a normal distribution. We take it from whatever distribution the population we sample from happens to be. We assume, often, that the distribution is normal, because that is mathematically convenient. But that does not make the sample or population distribution normal. And if the real population is not normal, and that is common, the statistics we use that assume a normal distortion will be wrong to some extent. This is particularly obvious with outlier analysis which commonly assumes normal distribution - when the distribution is not normal the outliers you generate won't really be outliers from the actual population you sampled from.

With large samples normality rarely if ever matters because statistics are asymptotically correct even with non-normality (this is tied in part to the central limit theorem).