ADMS 2320 Study Guide - Final Guide: Covariance, Lincoln Near-Earth Asteroid Research, Analysis Of Variance
3 Feb 2014
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Central limit theorem the sampling dist of the mean of a random sample drawn form any population is approximately normal for a sufficiently large sample size. The larger the sample size, the more closely the sampling distribution of x will resemble a normal distribution. Standard error of the proportion= p(1- p) / n. N - 1 se finite population; 2nd correction factor. Stn. error |difference b/w 2 sample means: z score (standardized score) | difference between 2 sample means: 1 a = level of confidence, a= significance level. Confidence interval estimator of m z-estimate of s z a. An unbiased estimator of a population is an estimator whose expected value is equal to that parameter. It is said to be consistent if the difference between the estimator and the parameter grows smaller as the sample size grows larger. If there are two unbiased estimators of a parameter, the one whose variance is smaller is said to be relatively efficient.
