Gaussian Random Generator

Generate random numbers following a normal (Gaussian) distribution with your specified mean and standard deviation.

What Does This Tool Do?

Unlike uniform random numbers (equally likely anywhere in a range), Gaussian/normal distribution produces numbers clustered around a mean, following the famous bell curve. This is how many real-world measurements are distributed.

Key Features

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Bell Curve

Numbers cluster around the mean following normal distribution.

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Custom Parameters

Set mean, standard deviation, count, and decimal places.

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Statistics Ready

Output suitable for statistical testing and simulation.

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Instant

Generates up to 1000 numbers immediately.

How to Use This Tool

Set the mean (center of distribution).
Set the standard deviation (spread).
Choose how many numbers to generate.
Click Generate.

How It Works

Uses the Box-Muller transform to convert uniform random numbers to normally distributed numbers: z = √(-2 ln U) × cos(2π V) where U and V are uniform random values.

Common Use Cases

💡 Statistical Simulation

Generate test data that matches real-world distributions.

💡 Testing Algorithms

Test sorting or search algorithms with realistic data.

💡 Monte Carlo Methods

Use normally distributed inputs for Monte Carlo simulations.

Frequently Asked Questions

What is standard deviation?

Standard deviation measures the spread. ~68% of values fall within 1 standard deviation of the mean, ~95% within 2, ~99.7% within 3.

How is this different from uniform random numbers?

Uniform random numbers are equally likely anywhere in a range. Gaussian numbers cluster around the mean — values far from the mean are rare.

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