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

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