Sampling Distribution

3 Pages
Unlock Document

Operations Management and Information System
OMIS 2010
Alan Marshall

Sampling DistributionsSampling Distributions of the MeanIs created by sampling draw sample of same size from a population or use rules of probability and laws of expected value and variance to derive sampling distributionSampling distribution of rolling a die can be created by drawing samples of size 2 tossing two diceoMean of sampling distribution of x bar is same as mean of population of toss of a die oVariance of sampling distribution of x bar is half of variance of population of the toss of a dieVariance of sampling distribution of sample mean is variance of population divided by sample size Standard error of the mean standard deviation of sampling distribution for infinitely large populationsAsof throws of the die increases probability that sample mean will be close to population mean increases oSampling distribution of x bar becomes narrower as n increases sampling distribution becomes increasingly bellshapedCentral limit theorem sampling distribution of mean of random sample drawn from any population is about normal for sufficiently large sample sizeoLarger the sample size more closely t
More Less

Related notes for OMIS 2010

Log In


Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.