Lecture 20 - 211 Fall 2009

# Lecture 20 - 211 Fall 2009 - I Introduction II Descriptive...

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± 1 I. Introduction II. Descriptive Statistics III. Probability, Random Variables and Sampling Distributions. A. Probabilty (Chapter 5) B. Random Variables (Chapter 5) C. Normal Distribution (Chapter 6) D. Sampling Distribution (Chapter 7) ± Theoretical distribution, a mathematical model. • Discrete Random variables - generated by processes • Theoretical distribution – mathematical model 3. Binomial Distributions Theoretical distribution of the process. • No experimentation or survey necessary – theoretical distribution gives probabilities. Processes satisfy binomial conditions. ± Special case of a discrete random variable. ± Gives probabilities for x successes in n trials ± Series of n Bernoulli Trials: 3. Binomial Distributions

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± 2 ± Binomial Probabilty Formula – mathematical model of the process: () ( 1 ) nx n x nxn x PC C −− 3. Binomial Distributions xx P x C pp C pq =− = ± Binomial Probabilty Formula – two parts represent two rules of probability : ( 1 ) n x x Px C p p 3.
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## This note was uploaded on 12/08/2011 for the course ECON 211 taught by Professor Daniellass during the Spring '11 term at UMass (Amherst).

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Lecture 20 - 211 Fall 2009 - I Introduction II Descriptive...

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