MATH 1780 Lecture Notes Chapter 3 Section 1

# MATH 1780 Lecture Notes Chapter 3 Section 1 - MATH 1780...

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MATH 1780: Introduction to Probability Instructor: Jason Snyder

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Contents Section 1: Random Variables and Their Probability  Distributions Section 2: Expected Values of Random Variables Section 3: The Bernoulli Distribution Section 4: The Binomial Distribution Section 5: The Geometric Distribution Section 6: The Negative Binomial Distribution Section 7: The Poisson Distribution Section 8: The Hypergeometric Distribution Section 9: The Moment-Generating Function Section 10: The Probability-Generating Function
Most of the experiments that we encounter  generate outcomes that can be thought of as real  numbers, such as height, number of relays closing  properly, and number of accidents during a  specific time interval.  These numerical outcomes, whose values can  change from experiment to experiment, are called  random variables .

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Example 1:  Suppose there are three relays in  parallel on a portion of a circuit diagram.  After a  switch is thrown each relay will either close  properly or malfunction and remain open.  Let X  represent the number of relays which close  properly.   X is an example of a random variable.
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## This note was uploaded on 09/30/2008 for the course MATH 1780 taught by Professor Snyder during the Fall '08 term at North Texas.

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MATH 1780 Lecture Notes Chapter 3 Section 1 - MATH 1780...

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