You learned in earlier chapters that you can convert a percentage to a decimal and multiply by a number to find that percentage of the number. You’ll use that same skill to find the expected value of a variable, .
The expected value is a way to describe what you should expect from a situation with probabilities. It’s a weighted result: outcomes with higher probability count more than outcomes with lower probability.
Now, let’s make one important point clear:
The expected value is not the same as the mean value.
You’ll use expected value when the problem gives probabilities and asks for what you can expect overall.
Now, let’s see how to calculate it.
To find the expected value, calculate the sum of each possible value multiplied by its probability.
Let’s use an example.
| Day of the week | Chance of rain | Predicted height of rainfall (inches) |
| Monday | 20% | 2 |
| Tuesday | 10% | 1 |
| Wednesday | 0% | 0.5 |
| Thursday | 35% | 0.5 |
| Friday | 35% | 1 |
Using the table of data above and assuming that it will rain one day next week, what is the expected height of rainfall in inches?
Go row by row:
You can think of it like this: “There’s a 20% chance of 2 inches on Monday, a 10% chance of 1 inch on Tuesday, …”
The expected height of rainfall on any given day is inches.
Here is the general formula. is the expected value, each is a possible value, and each is the probability of that value.
In the rainfall example, was inches and was (or ). You multiplied each outcome by its probability and added the results, exactly as the formula shows.
Now try a simpler example.
What is the expected value of given it has the following values and probabilities?
| 4 | 22% |
| 2 | 45% |
| 1 | 10% |
| 6 | 7% |
| 7.5 | 14% |
| 10 | 2% |
Using the formula
the expected value is .
In these problems, the probabilities should add up to . When they do, the expected value should fall between the smallest and largest values in the table.
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