What probability distributions are supported?

You can use normal, uniform, lognormal, and triangular distributions to model your input variables.

How do I write the output formula?

Use standard arithmetic operators (+, -, *, /, %, ^), parentheses, and functions like abs, sqrt, exp, log, min, max, or pow, along with constants like PI and E.

Can I make my simulation results reproducible?

Yes, by entering a value in the optional random seed field, the generator will produce the exact same sequence of random trials every time.

What is the maximum number of trials I can run?

You can run up to 200,000 trials per simulation for highly accurate and smooth distribution curves.

What statistics does the tool calculate?

The tool outputs the mean, median, standard deviation, a custom confidence interval range, and the probability of the outcome being greater than zero.

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Data Analysis

Monte Carlo Simulation Builder

Define input distributions (normal/uniform/lognormal/triangular), write a formula, run thousands of trials, and get the output distribution histogram with confidence intervals.

Details

What this tool helps you do

Build custom Monte Carlo simulations by combining random inputs (normal/uniform/lognormal/triangular), a formula over variable names, and N trials. Returns histogram, mean/median/std, confidence intervals and P(outcome>0).

Execution

Run this tool

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Prepared example runs

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2 examples

Project profit (revenue − cost)

Revenue normal [100,20], cost uniform [30,50].

<div class="mc-wrap">10,000 seeded trials. Mean 59.9599, median 60.1987, std dev 20.7086, 90% CI [25.8798, 93.717], P(outcome > 0) = 99.8%.</div>

Circle area from noisy radius

Radius ~ normal [5, 0.5], area = π·r².

<div class="mc-wrap">20,000 seeded trials. Mean 79.3635, median 78.5676, std dev 15.7396, 95% CI [50.7869, 112.3056], P(outcome > 0) = 100.0%.</div>

Inputs

Set the required fields, then run the tool.

5 options

ContentPaste or type the main input values.3

Distributions (one per line: name = type [params])textareaRequiredDeclare each random input. Types: normal [mean, sigma], uniform [min, max], lognormal [mu, sigma], triangular [a, b, c].Output formulatextRequiredArithmetic expression over the variable names. Supports + - * / % ^, parentheses, abs/sqrt/exp/log/min/max/pow, PI, E.Random seed (optional, for reproducibility)textOptionalA fixed seed makes results reproducible run-to-run. Leave blank for a fresh random draw.

SettingsAdjust formats, ranges, numbers, and modes.2

Number of trialsnumberOptionalHow many samples to draw. More trials → smoother histogram (100 – 200000).Confidence level (%)numberOptionalConfidence interval percentile band (50–99.9%). Default 90% → P5–P95.

Result

Ready for a run

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Samples

Monte Carlo Simulation Builder

What this tool helps you do

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Prepared example runs

Inputs

Result

Examples that match this tool

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Prepared example runs

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Key facts

Overview

When to use

How it works

Use cases

Examples

1. Project Profit Margin Risk Analysis

2. Geometric Tolerance Simulation

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