STAT 2040 Lecture Notes - Lecture 7: Minimum-Variance Unbiased Estimator, Bias Of An Estimator, Central Limit Theorem

• School: University of Guelph
• Department: Statistics
• Course: STAT 2040
• Professor: Jeremy Balka

Document Summary

Sample mean is an estimation of population mean. The sampling distribution of a statistic is the probability distribution of that statistic (the distribution of the statistic in all possible samples of the same size). The mean of the sampling distribution of distribution from which we are sampling is equal to the mean of the n=sample size. If the distribution from which we are sampling is normal, the sampling distribution of is normal. *ch6 if the distribution from which we are sampling is normal, then distributed. *the central limit theorem the distribution of will be approximately normal, regardless of the distribution from which we are sampling, provided the sample size is large. (rough guideline) is normally. Approx. normal use normal distr (area under curve) The true standard deviation of the sampling distribution of. In practice, the true sd, var, mean of the sampling distr" is almost always unkown. Standard error of sample mean, (estimated sd of sample distr" of.