Stat 217 – Day 11Recap – Selecting SamplesRecap – Random SamplingDemo – Gettysburg AddressCentral Limit TheoremSampling in RealityTo DoStat 217 – Day 11Sampling IssuesRecap – Selecting SamplesIf a sampling method consistently overestimates or consistently underestimates the population parameter, then the sampling method is biased.Recap – Random SamplingSimple random sampling (every member of the population is equally likely to be selected) or other random sampling methods are a way to ensure that the sampling method is not biased and provide a convincing argument that the sample can be considered representative of the larger population.Demo – Gettysburg AddressCentral Limit TheoremIf the sample size is large enough…n > 10 and n (1- ) > 10 … then the distribution of sample proportions can be approximated by the normal distribution with mean and standard deviation .37(1-.37)/20) = .108n/)1(Sampling in RealityCan reduce “sampling bias” by taking random sampleCan reduce “random sampling errors” by taking larger sampleCan reduce “nonsampling bias” by using care!To DoPrelab 3Reading 7Turn in Investigation 3Ok to just turn in hard copy of last
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