Enter outcomes, assign probabilities, and verify normalized totals. See mean, variance, spread, and probability plots. Export clean results for reports, classes, audits, or reviews.
Use the form below to estimate the expected value of a discrete random variable. The page remains single column, while the input grid changes across screen sizes.
| Label | Outcome | Probability | Contribution |
|---|---|---|---|
| A | 0 | 0.10 | 0.00 |
| B | 1 | 0.20 | 0.20 |
| C | 2 | 0.40 | 0.80 |
| D | 3 | 0.30 | 0.90 |
| Expected Value | 1.90 | ||
This sample uses a valid discrete distribution because the probabilities sum to 1. The expected value equals the sum of all outcome-probability products.
For a discrete random variable, the expected value is the weighted average of all possible outcomes.
Expected value: E(X) = Σ[x × p(x)]
Second moment: E(X²) = Σ[x² × p(x)]
Variance: Var(X) = E(X²) - (E(X))²
Standard deviation: σ = √Var(X)
If the entered probabilities do not total 1, you can normalize them. Normalization divides each probability by the total sum before calculation.
Expected value is the long-run average outcome of a discrete random variable. It weights each possible value by its probability, then adds those weighted outcomes together.
Yes. A valid discrete probability distribution totals 1. This calculator can also normalize entries automatically when the checkbox is enabled.
Yes. Choose percent mode, then enter values like 25 for 25%. The calculator converts them into decimal probabilities before computing the expected value.
Expected value is a weighted average. Averages often fall between listed outcomes, so the result does not need to match any single possible value.
Variance measures weighted spread in squared units. Standard deviation is the square root of variance, so it returns spread in the original outcome units.
Yes. Outcomes may be positive, zero, or negative. The only restriction is that probabilities cannot be negative and must form a valid total.
Normalize when your entries are meant to represent relative likelihoods but do not total 1 due to rounding or partial raw inputs.
The chart plots the discrete probability distribution. It helps you see which outcomes carry more probability mass before interpreting the expected value.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.