Lecture4 - Lecture 4: Poisson Approximation to Binomial...

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Unformatted text preview: Lecture 4: Poisson Approximation to Binomial Distribution; Measures of Center and Variability for Data (Sample); Chapter 2 No Lab this week, but Questions in Lab# 2 are related to this weeks topics Hw#2 is due by 5pm, next Monday Poisson Approximation for the Binomial Distribution For Binomial Distribution with large n , calculating the mass function is pretty nasty So for those nasty large Binomials (n 100) and for small (usually 0.01), we can use a Poisson with = n ( 20) to approximate it! Example Density (for Continuous) and Mass (for Discrete) functions tell you the chance/proportion/probability that a variable takes a certain value Need to know the distribution expression both used to rigorously describe populations or processes How to know which distribution is applicable? See Chapter 2 Numerical measures for both samples and populations Bring Your Calculator from now on 2.1 Measures of Center (Data) The sample mean arithmetic average...
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Lecture4 - Lecture 4: Poisson Approximation to Binomial...

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