Random Variables and Discrete Probability Distributions

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Raffle Example • Next, we determine the probability that each outcome occurs. �� P(X = $0) = 993/1000 since there are 993 prizes of $0, that is, there are 993 non-winning non winning tickets, <strong>and</strong> one thous<strong>and</strong> tickets were sold.
Raffle Example • Finally, we compile the information into a table
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Random Variables and Discrete Proba
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Random Variable • A random variab
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Random Variable • A discrete rand
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Random Variable • A continuous ra
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Probability Distribution for a Disc
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What is the probability distributio
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Page 57 and 58: Did you notice that each example me
Page 59 and 60: Requirements for a probability dist
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Page 63 and 64: Did you notice that if the examples
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Page 67 and 68: Notation • For clarity, we will u
Page 69 and 70: Does the table below represent a pr
Page 77 and 78: Probability Histogram • As with a
Page 79 and 80: Raffle Example • Although there a
Page 81 and 82: Raffle Example • Since not not wi
Page 83 and 84: Raffle Example • Next, we determi
Page 85 and 86: Raffle Example • Next, we determi
Page 87: Raffle Example • Next, we determi
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Page 93 and 94: Raffle Example • We do not need t
Page 95 and 96: Raffle Example • Winnings Winning
Page 97 and 98: Raffle Example • Alternate Altern
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Page 105 and 106: Raffle Example • Note: The point
Page 107 and 108: Raffle Example • Did you notice t
Page 109 and 110: Raffle Example • Did you notice t
Page 111 and 112: Expected Value for a Discrete Rando
Page 119 and 120: How many Heads should we expect if
Page 125 and 126: What is the expected value for the
Page 131 and 132: What is the expected prize for our
Page 137 and 138: What are the expected winnings for
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What are the expected winnings for
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What are the expected winnings for
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For our raffle example, can we use
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Variance and Standard Deviation for
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What is the standard deviation for
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Variance and Standard Deviation for
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Random Variables and Discrete Probability Distributions

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