Visualize Random Samples from Continuous Distributions
Effortlessly generate and visualize random samples from any continuous probability distribution. Simply input the Probability Density Function (PDF), interval, and the number of samples.
Define the PDF as a function of x. Use JavaScript syntax.
Specify the interval from where samples will be generated. Format: [min, max].
Enter the desired number of random samples to generate.
Generated Random Samples
Distribution Visualization
Understanding Continuous Distributions
A continuous probability distribution describes probabilities of the possible values of a continuous random variable. Unlike discrete distributions, continuous distributions deal with variables that can take any value within a given range. The Probability Density Function (PDF), denoted as f(x), represents the relative likelihood of the random variable taking a specific value. The area under the PDF curve over an interval gives the probability that the variable falls within that interval. This tool uses the Rejection Sampling method to generate random samples that follow the shape defined by your PDF, allowing you to visualize and explore different continuous distributions.
- PDF (Probability Density Function): Defines the shape of the distribution.
- Interval: The range [min, max] within which random samples are generated.
- Rejection Sampling: A method used to sample from probability distributions.
Learn more about continuous distributions on resources like Wikipedia.