ec41lecture7

Ec41lecture7 - Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshevs Inequality Linear Functions of Independent Random

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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Statistics for Economists Lecture 7 Kata Bognar UCLA October 19, 2010
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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Announcements Answer key for the midterm is online. Homework 3 will be posted on Thursday.
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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Last Lecture Special discrete distributions
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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Today’s Outline 1 Expectations 2 Chebyshev Theorem 3 Linear functions of random variables 4 Readings: TH, Chapter 2.2, 2.5 5 Readings for next class: TH, Chapter 2.4
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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Functions of a Random Variable Let X be a discrete random variable with p.m.f. f ( x ) . Then Y = u ( X ) is a random variable that takes the value u ( x ) - for all x in the support of X - with a probability f ( x ) . Example: X has a p.m.f. f ( x ) = x 6 for x = 1 , 2 , 3 . Y = 2 X takes y = 2 , 4 , 6 with probabilities 1 6 , 2 6 , 3 6 . Y has a p.m.f. g ( y ) = y 12 for y = 2 , 4 , 6 .
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Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshev’s Inequality Linear Functions of Independent Random Variables Functions of a Random Variable X Y = 2 X x f ( x ) 1 1/6 2 2/6 3 3/6 = y g ( y ) 2 1/6 4 2/6 6 3/6
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This note was uploaded on 12/28/2010 for the course ECON 41 taught by Professor Guggenberger during the Fall '07 term at UCLA.

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Ec41lecture7 - Statistics for Economists Lecture 7 Kata Bognar UCLA Expectations Chebyshevs Inequality Linear Functions of Independent Random

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