Statistics · Distributions

Multinomial Distribution Calculator

Evaluate the exact probability and category moments for a complete vector of counts from repeated categorical trials.

Statistics · Distributions

Enter your statistical inputs

Private in-browser calculation · explicit assumptions
Discrete support uses separate whole-number outcomes; probability is carried by the individual masses.
0support10
  1. 1EnterProvide the known values
  2. 2CalculateResults update automatically
  3. 3VerifyReview the details and units
Try an example

Enter plain numbers without measurement units. Datasets accept commas, spaces, semicolons, or line breaks and are limited to 10,000 values. Results stay in this browser.

Statistics result

Enter valid values to see the result.

Your entries are calculated in this browser and are not submitted to 365CALCS.COM.

Feedback

Understand the distribution

What the multinomial distribution calculator models

Assigning probability to separate outcomes. A discrete probability mass function assigns probability directly to each allowed count or category combination. All mutually exclusive masses across the full support sum to one.

Probability mass rule

P(X₁=x₁,…,Xₘ=xₘ)=n!∏pᵢ^xᵢ/xᵢ!, with Σxᵢ=n and Σpᵢ=1.

A probability mass is a probability at an allowed discrete outcome.

Interpretation and limits

Category counts are dependent because they must sum to the fixed total even when trials are independent.

Model boundary: Trials must be independent with stable mutually exclusive exhaustive category probabilities, and the aligned probability list must total one.

Quick guide

How to use this calculator

  1. Enter the observations, probabilities, model parameters, or summary statistics requested by the visible labels.
  2. Keep every value on the same scale and confirm that the selected sampling relationship, distribution, and tail convention match the question you are investigating.
  3. Read the result together with its assumptions and interpretation. Statistical output summarizes uncertainty under a model; it does not repair biased data or establish causation.

Calculation method

How the multinomial distribution calculator works

P(X₁=x₁,…,Xₘ=xₘ)=n!∏pᵢ^xᵢ/xᵢ!, with Σxᵢ=n and Σpᵢ=1.

Category counts are dependent because they must sum to the fixed total even when trials are independent.

Worked example

Multinomial Distribution example

Counts 2, 1, 1 with probabilities 0.5, 0.25, 0.25 have joint probability 0.1875.

P(X₁=x₁,…,Xₘ=xₘ)=n!∏pᵢ^xᵢ/xᵢ!, with Σxᵢ=n and Σpᵢ=1.

Supported inputs

Precision and limits

Model and design

Trials must be independent with stable mutually exclusive exhaustive category probabilities, and the aligned probability list must total one.

Numerical scope

Inputs use double-precision numerical methods with guarded domains. Datasets accept up to 10,000 finite plain-decimal values. Extremely large parameters or probabilities deep in a numerical tail may require specialist statistical software.

Interpretation

Category counts are dependent because they must sum to the fixed total even when trials are independent.

Decision boundary

The calculator does not validate how data were collected, diagnose dependence or bias, choose a scientifically meaningful effect, or replace review by a qualified statistician for consequential research, medical, regulatory, safety, or policy decisions.

Privacy

Entered values and calculated results stay in this browser and are not sent to an analytics service.

Continue calculating

Related calculators