lecture7.pdf - COMPSCI 240 Reasoning Under Uncertainty Arya...

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COMPSCI 240: Reasoning Under Uncertainty Arya Mazumdar University of Massachusetts at Amherst Fall 2016
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Lecture 7
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Polls Pace of the class: 155 Students 85 voted
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Polls Pace of the class: 155 Students 85 voted It is optimum now 33 Slow down 49 Go faster 3 I do not care (did not vote) 70
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Polls Pace of the class: 155 Students 85 voted It is optimum now 33 Slow down 49 Go faster 3 I do not care (did not vote) 70 Randomly pick up a student. What is the probability that he/she did not vote?
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Polls Pace of the class: 155 Students 85 voted It is optimum now 33 Slow down 49 Go faster 3 I do not care (did not vote) 70 Randomly pick up a student. What is the probability that he/she did not vote? 70 155 = 0 . 4516
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Polls Slides or White-board: 155 Students 86 voted
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Polls Slides or White-board: 155 Students 86 voted Current use is optimum 33 Use White-board more 39 Use White-board less 14 I do not care (did not vote) 69
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Polls Slides or White-board: 155 Students 86 voted Current use is optimum 33 Use White-board more 39 Use White-board less 14 I do not care (did not vote) 69 Randomly pick up a student. What is the probability that he/she thinks current use is optimum?
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Polls Slides or White-board: 155 Students 86 voted Current use is optimum 33 Use White-board more 39 Use White-board less 14 I do not care (did not vote) 69 Randomly pick up a student. What is the probability that he/she thinks current use is optimum? 33 155 = 0 . 21
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Other points
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Other points Math basics for the class
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Other points Math basics for the class Posting slides earlier
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Other points Math basics for the class Posting slides earlier Programming assignments
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Probability mass functions The probability associated with the event { X = x } for each element x R of a discrete random variable X is referred to as the probability mass function or PMF of the random variable.
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Probability mass functions The probability associated with the event { X = x } for each element x R of a discrete random variable X is referred to as the probability mass function or PMF of the random variable. The probability mass function is denoted by P ( X = x ) or p X ( x )
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Probability mass functions The probability associated with the event { X = x } for each element x R of a discrete random variable X is referred to as the probability mass function or PMF of the random variable. The probability mass function is denoted by P ( X = x ) or p X ( x )
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Bernoulli Random Variables Suppose we have an experiment with two outcomes H and T . H happens with probability (1 - p ) and T with probability p .
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Bernoulli Random Variables Suppose we have an experiment with two outcomes H and T . H happens with probability (1 - p ) and T with probability p .
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