7. Modeling Randomness
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The expected value is given by the sum of each outcome's value multiplied by its probability.
See solution.
The expected value is given by the sum of each outcome's value multiplied by its probability. We first begin by giving an example. Then we will explain the meaning of the expected value.
Outcome X | Probability of X, P(X) | X⋅P(X) |
---|---|---|
2 | 361 | 2⋅361=362 |
3 | 362 | 3⋅362=366 |
4 | 363 | 4⋅363=3612 |
5 | 364 | 5⋅364=3620 |
6 | 365 | 6⋅365=3630 |
7 | 366 | 7⋅366=3642 |
8 | 365 | 8⋅365=3640 |
9 | 364 | 9⋅364=3636 |
10 | 363 | 10⋅363=3630 |
11 | 362 | 11⋅362=3622 |
12 | 361 | 12⋅361=3612 |
Sum of Values | 36252=7 |
Therefore, the expected value is 7.
We found that the expected value of rolling two fair dice and finding their sum is 7. This means that if we repeat the experiment an infinite number of times, the expected value is 7. Similarly, for any experiment, the expected value tells us what we expect to happen if the experiment is conducted a certain number of times. This can help us to make decisions based on data.