(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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View Full DocumentProbability 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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 Spring '08
 MARTIN
 Probability theory, Max=4 Max=4 Max=4, legitimate PMF, Random Variables Random, PMF chart

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