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Unformatted text preview: Midterm 2 Overview by Chapter Chapter 4 Continuous distributions Families: Identification, domains, expected value variance: See Summary Probability problems: R script: Normal Distribution, Exponential Distribution, Gamma Distribution Hand integration: Simple polynomial density Chapter 5 Joint Distributions Bivariate Distribution: both Discrete, both Continuous Find Marginal and Conditional Distributions Find E(X), Var(X), and probabilities for intervals Independence Expected Values Covariance and Correlation Statistics and their distribution for Random Samples Know and understand definition of Random Samples Understand obtaining the distribution for any statistic computed from random sample from a known discrete distribution Know about the distributions of a random sample mean and a random sample sum How they relate to the population mean, , variance , and sample size n. ) = , ,...
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This note was uploaded on 12/20/2011 for the course STAT 344 taught by Professor Staff during the Spring '08 term at George Mason.
 Spring '08
 Staff
 Normal Distribution, Probability, Variance

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