RVs&Expectation - (5.1 5.2 Discrete Random...

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(5.1, 5.2) Discrete Random Variables Random Experiment: create an outcome space consisting of ALL possible outcomes, such as flipping a coin or rolling dice. Random Variable: function that takes all the outcomes and assigns probabilities. Example : All Outcomes: 36 outcomes for rolling 2 dice. The function: “sum” or “max” of the 2 dice. Event: sum = 3 or max = 4 X= sum of two dice P(X=3) = Y=max of 2 dice P(Y=4) = 1 2 3 4 5 6 1 Sum=3 Max=4 2 Sum=3 Max=4 3 Max=4 4 Max=4 Max=4 Max=4 Max=4 5 6 R.V. number of times you look at the clock during class Event : look at the clock less than 5 times R.V. length of time to complete a problem Event : you complete a problem within 6 and 8 minutes Discrete Countable Continuous Not Countable Number of students coming to class Number of free throws until you make a shot Time you can hold your breath Lifetime of cell phone battery
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Probability Mass Function (PMF): This will be a generic formula given a random variable that will find the probability of a certain event. For the finite discrete case one can often make a chart to display the probability.
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RVs&Expectation - (5.1 5.2 Discrete Random...

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