so a sampling distribution is a distribution of the mean of many samples takes from the underlying popuulation with same sample size.
1)so taking alot of samples from the population would mean that u have access to the entire population, so why not just calculate the population mean and S.D itself?
2)when we do not have access to the opoulation S.D which we ideally dont have we take the S.D of the sample to calculate the standard error of the sample mean, but which sample’s S.D is taken to calculate the standard error?
It doesn’t mean that at all. You grab 500 giraffes and calculate their average heights. I grab 500 giraffes (which may include some of the ones you grabbed) and measure their average height. Blackjack grabs 500 giraffes (which may include some of the ones you grabbed, and some of the ones I grabbed) and measures their average height, and so on. Nobody can grab all of the giraffes in the world.
You take yours, I take mine, Blackjack takes his, and so on. They’ll likely all be different, but close.
ok so in real world statistics is it like india_28( the head of the operation) would send u me and blackjack to grab 500 giraffes each and ask us to calculate there mean and s.d and bring the info back to him and he will than compile the data and calculate the distn mean and s.d than?
What is this SD called? I know that the mean is the mean of the sampling distribution. Err, wait what would be the mean of a sampling distribution? What is its significance?
S.d means the standard deviation of the sampling distribution and mean of the sampling distribution is the mean of all the samples u took to construct the distribution(its usaully provided in the question) its significance ummm.its assumed that the mean of sampling distn is the mean of the popn
