Probstat/notes/random variables
- This is part of probstat.
In many cases, after we perform a random experiment, we are interested in certain quantity from the outcome, not the actual outcome. In that case, we can define a random variable, which is a function from the sample space to real numbers, to represent the random quantity that we are interested in.
For example, consider the following experiment. We toss two dice. Let a random variable X be the sum of the values of these two dice. The table below shows the outcomes and probabilities related to X.
i | Outcomes for which X = i | Probability P{ X = i } |
2 | (1,1) | 1/36 |
3 | (1,2), (2,1) | 2/36 |
4 | (1,3), (2,2), (3,1) | 3/36 |
5 | (1,4), (2,3), (3,2), (4,1) | 4/36 |
6 | (1,5), (2,4), (3,3), (4,2), (5,1) | 5/36 |
7 | (1,6), (2,5), (3,4), (4,3), (5,2), (6,1) | 6/36 |
8 | (2,6), (3,5), (4,4), (5,3), (6,2) | 5/36 |
9 | (3,6), (4,5), (5,4), (6,4) | 4/36 |
10 | (4,6), (5,5), (6,4) | 3/36 |
11 | (5,6), (6,5) | 2/36 |
12 | (6,6) | 1/36 |
A random variable X also induces events related to it. From the previous example, the event that X=10 corresponds to the subset {(4,6), (5,5), 6,4)} of the sample space. Also, if the event X >= 11 corresponds to {(5,6), (6,5), (6,6)}. Therefore, it is reasonable to consider the probability of events defined by random variables. From the two-dice example, we have P{ X >= 11 } = 3/36.