Lecture 17 - 211 Fall 2009

# Lecture 17 - 211 Fall 2009 - s 1 I Introduction II...

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Unformatted text preview: s 1 I. Introduction II. Descriptive Statistics III. Probability, Random Variables and Sampling Distributions. A. Probabilty (Chapter 5) 1. Basic Concepts. 2. Rules of Probability. B. Random Variables (Chapter 5) C. Normal Distribution (Chapter 6) D. Sampling Distribution (Chapter 7) s Rule 6: Conditional Probability • The probability that an event will occur given that some other event has occurred. • Example: ( 5 ) ( 5 ) ( ) P G SO P G SO P SO = & 2. Rules of Probability s Conditional Probability: Given one of the individual events has occurred, what is the probability of the other individual event? Eg., what is P(G5|SO)? Exam 1 Grade Class FR SO JR SR OT Totals < 60 0.024 0.047 0.031 0.000 0.000 0.102 60 < 70 0.027 0.068 0.027 0.014 0.000 0.136 70 < 80 0.031 0.108 0.081 0.007 0.000 0.227 80 < 90 0.034 0.217 0.051 0.031 0.003 0.336 90 and over 0.031 0.102 0.044 0.020 0.003 0.200 Totals 0.146 0.542 0.234 0.071 0.007 1.000 s 2 s Conditional Prob. for Independent Events • Suppose event E 1 occurs. • If P( E 2 ) is not affected , then E 1 and E 2 are independent events ....
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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 17 - 211 Fall 2009 - s 1 I Introduction II...

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