Statistik

Hypergeometric Probability Calculator

Easily calculate hypergeometric probability online. Determine the probability of successes in a sample without replacement. Free, accurate, and user-friendly hypergeometric distribution calculator.

Understanding Hypergeometric Probability

The hypergeometric distribution is used when we sample without replacement from a finite population. It helps calculate the probability of getting a specific number of successes in our sample.

$$P(X=k) = rac{{inom{K}{k} inom{N-K}{n-k}}}{{inom{N}{n}}}$$
  • \(N\): Total population size
  • \(K\): Number of successes in the population
  • \(n\): Sample size (number of draws)
  • \(k\): Number of successes in the sample (what we want to find the probability for)

Result:

Probability:

Error:

Understanding Hypergeometric Probability

The Hypergeometric Probability Calculator is a tool designed to compute the probability of achieving a specific number of successes in a sample drawn without replacement from a finite population. This is particularly useful in scenarios where selections are made without returning items to the population, such as in quality control, lottery drawings, and card games.

Key Concepts:

  • Population Size (N): The total number of items in the population from which you are drawing a sample.
  • Number of Successes in Population (K): The count of items in the population that are considered 'successes'.
  • Sample Size (n): The number of items drawn from the population without replacement.
  • Number of Successes in Sample (k): The exact number of 'successes' you are interested in finding the probability for within your sample.

For example, if you want to know the probability of drawing exactly 3 aces (successes) from a deck of 52 cards (population) when you draw 5 cards (sample) and there are 4 aces in the deck (successes in population), you would use this calculator.

The formula used is based on combinations and calculates the ratio of favorable outcomes to total possible outcomes in a hypergeometric distribution scenario.