Expected value & variance
Average outcomes, spread, and the binomial count.
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the idea
A random variable is a number decided by chance, like a game's payout. Its expected value is the long-run average: weight each value by its probability and add.
The variance is the average squared distance from that expected value, and its square root is the standard deviation. A binomial count is the number of successes in n independent tries, each with the same chance p. Its mean is np and its variance is np(1 − p).
techniques
Weight and add
- Expected value: multiply each value by its probability and add. Keep any minus signs.
- Mean of the squares: the same, with each value squared.
- Variance: the mean of the squares minus the expected value squared.
worked example
X is 0 with probability 0.8 and 5 with probability 0.2. What is the variance of X?
- Expected value: 5 × 0.2 = 1.
- Mean of the squares: 25 × 0.2 = 5.
- Variance: 5 − 1 × 1 = 4.
Answer: 4
One order, times the orders
- One order: p for each success and 1 − p for each failure, multiplied.
- Number of orders: C(n, k), the ways to choose which k tries succeed.
- Multiply the two and reduce.
worked example
You flip a fair coin 4 times. What is the probability of exactly 2 heads? Answer as a fraction.
- One order, like HHTT: 1/2 × 1/2 × 1/2 × 1/2 = 1/16.
- Orders: C(4, 2) = 6.
- 6 × 1/16 = 6/16 = 3/8.
Answer: 3/8
Binomial mean and spread
- Mean: n × p.
- Standard deviation: the square root of n × p × (1 − p). Round only at the end.
worked example
An event has a 25% chance on each of 200 independent trials. What is the standard deviation of the number of successes? Round to 2 decimal places.
- Variance: 200 × 0.25 × 0.75 = 37.5.
- The square root of 37.5 ≈ 6.12.
Answer: 6.12
watch out for
- Averaging the values and ignoring the probabilities.
- Giving the standard deviation when the question asks for the variance, or the other way round.
- Finding the chance of one particular order and forgetting the others. Exactly 3 heads in 5 flips can happen in 10 orders.
practice
Expected value
worked example
X is 76 with probability 0.25 and 19 with probability 0.75. What is the expected value of X?
Answer: 33.25
- Weight each value by its chance: 76 × 0.25 + 19 × 0.75
- = 19 + 14.25 = 33.25.
Variance
worked example
X is 9 with probability 0.3 and 19 with probability 0.7. What is the variance of X?
Answer: 21
- E[X] = 9 × 0.3 + 19 × 0.7 = 16.
- E[X²] = 81 × 0.3 + 361 × 0.7 = 277.
- Var(X) = E[X²] − (E[X])² = 277 − 256 = 21.
Exactly k successes
worked example
You flip a fair coin 6 times. What is the probability of getting exactly 1 head? Give the answer as a fraction in lowest terms.
Answer: 3/32
- There are C(6, 1) = 6 orders with exactly 1 head, each with chance (1/2)⁶ = 1/64.
- So the probability is 6/64 = 3/32.
Binomial mean & SD
worked example
Each item a machine makes has a 25% chance of being defective, independently of the others. A batch has 90 items. What is the standard deviation of the number of defective items in the batch? Round to 2 decimal places.
Answer: 4.11
- SD = √(np(1 − p)) = √(90 × 0.25 × 0.75) = √16.875 ≈ 4.1079, which rounds to 4.11.
- (The mean is np = 22.5.)