10_MT_2_concepts_tested_fall_11

10_MT_2_concepts_tested_fall_11 - Independent events and...

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Concepts you need to know for midterm two Chapter 12 Sampling and different types of bias in sampling Different types of sampling including simple random sample, stratified random sample, cluster sample, systematic sample, and multi-stage sample Population and sample, statistic and parameter, descriptive and inferential statistics Chapter 13 Observational designs, true experimental designs, randomized block designs Retrospective studies, prospective studies Control groups, blinding, blocking, random assignment Drawing of causal conclusions Chapter 14 Concept of probability of an event Concept of complement in probability Disjoint or mutually exclusive events Addition rule for disjoint events
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Unformatted text preview: Independent events and multiplication rule Chapter 15 More on disjoint events, overlapping events Conditional probability and Baye’s Rule Conditional probability and independence Tree diagrams as another mean of understanding conditional probability Chapter 16 Mean, expected value, variance, and standard deviation of discrete random variables Probability models for discrete random variables Effects of linear transformation on mean, variance, and standard deviation Mean and variance of the sum and difference of two random variables Chapter 17 Bernouli trial and the binomial model Approximation of the binomial by normal...
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This note was uploaded on 12/03/2011 for the course STATISTICS 10 taught by Professor Gould during the Fall '11 term at UCLA.

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