ADMS 2320 Study Guide - Final Guide: Central Limit Theorem, Sampling Distribution, Tachykinin Receptor 1
7 Oct 2011
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Document Summary
The methods of sampling plan: simple random, stratified, cluster. Sampling errors: different samples yield different sampling errors; may be positive or negative; expected sampling error decreases as sample size increases. Nonsampling error (3 types)= error in data acquisition, nonresponse errors, selection bias (increase in same size will not reduce this error). Central limit theorem: sampling distribution of mean of random sample from any population is approximately normal for sufficiently large sample size. The larger the sample size, the more closely the sampling distribution of sample mean will resemble normal distribution. Chebyshev"s theorem: any distribution, proportion of observation lying within standard deviation of mean is at least. If histogram is bell shaped, use empirical rule. 68% of all observation falls within one sd of mean. 95% falls within two sd of mean, approx. Mutually exclusive events: if o1 occurs, then o2 cannot occur; o1 and o2 have no common elements.
