Random Number Generator
Generate random numbers with uniform, normal (Gaussian), or exponential distributions. Visualize the distribution with histograms.
Random Number Generator
Generate random numbers with uniform, normal, or exponential distributions
Formula
X ~ U(min, max)Uniform distribution: equal probability for all values in range
Distribution Types
📊 Uniform
Equal probability for all values in range. Creates a flat histogram.
Use for: Random selection, shuffling, simulations
🔔 Normal
Bell curve centered at mean. Most values cluster near the center.
Use for: Natural phenomena, test scores, measurements
📉 Exponential
Rapid decay from zero. Models time between random events.
Use for: Wait times, equipment failure, decay processes
How to Use
- 1Choose distribution — Select uniform, normal, or exponential distribution.
- 2Set parameters — Configure the distribution parameters (range, mean, standard deviation, etc.).
- 3Set quantity — Choose how many random numbers to generate.
- 4Generate — Click Calculate to generate numbers and view the distribution.
Frequently Asked Questions
What is uniform distribution?
Uniform distribution means every value in the range has an equal probability of being selected. For example, rolling a fair die produces a uniform distribution from 1 to 6.
What is normal (Gaussian) distribution?
Normal distribution creates a bell curve where values cluster around the mean. About 68% of values fall within one standard deviation of the mean, and 95% within two standard deviations.
What is exponential distribution?
Exponential distribution models the time between events in a Poisson process. It's commonly used for modeling waiting times, equipment failure, and radioactive decay.
Are these truly random numbers?
These are pseudorandom numbers generated by JavaScript's Math.random() function. They are suitable for most applications but not for cryptographic purposes.
What is the rate parameter (λ) in exponential distribution?
Lambda (λ) is the rate parameter that determines how quickly the distribution decays. Higher λ means more values close to zero. The mean of an exponential distribution is 1/λ.