I am trying to extract a sample from a given population. Assuming the population distribution is normal (I still have to test it, but I am confident it is), since the number of observations in the population is too high to perform some tests I need to do with my laptop (N>50,000), I'd like to extract a smaller sample from it.
My questions are:
- What would be a good sampling method to avoid including values lying inthe tails of the population into the extracted sample and
- what would be the best sample size?
As far as I know, I thought random sampling won't let me achieve what I want in question 1, as the probability of picking up an outlier rather than a value closer to the mean is the same (although the number of my outliers is very low). Am I wrong?
Secondly, I know the estimation of the sample size depends on the error I want to allow. So, in the light of these few things I know, I am asking if someone could help me getting me a bit further into this, and hopefully providing some useful an to-the-point reference.
Thanks in advance to those who might want to help me clarifying this.