Statistics & probability
Sampling without replacement
Find success-count probabilities when drawing from a finite population.
A clear answer. Here’s how.
Uses the hypergeometric distribution for a simple random draw without replacement. Success items and draws cannot exceed population size. Shows exact and cumulative probabilities and the feasible success-count range. Log combination weights are normalised numerically; population size is limited to 10,000.
See a worked example
Worked example
A fixed demonstration, separate from the values you enter above.
- Population size
- 50
- Success items in population
- 10
- Number drawn without replacement
- 5
- Successes drawn k
- 2
Example result
- P(X = k)
- 0.209839717571
- P(X ≤ k)
- 0.951739696804
- P(X > k)
- 0.0482603031962
- P(X ≥ k)
- 0.258100020767
- Feasible success counts
- 0–5
- Model mean
- 1