Who discovered hypergeometric distribution?
The term HYPERGEOMETRIC (to describe a particular differential equation) is due to Johann Friedrich Pfaff (1765-1825) (Kline, page 489).
What is the hypergeometric distribution used for?
The hypergeometric distribution can be used for sampling problems such as the chance of picking a defective part from a box (without returning parts to the box for the next trial). The hypergeometric distribution is used under these conditions: Total number of items (population) is fixed.
What is the hypergeometric distribution in statistics?
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws, without replacement, from a finite population of size that contains exactly objects with …
What is the formula for hypergeometric distribution?
The hypergeometric distribution has the following properties: The mean of the distribution is equal to n * k / N . The variance is n * k * ( N – k ) * ( N – n ) / [ N2 * ( N – 1 ) ] .
Where does the name hypergeometric distribution come from?
Because these go “over” or “beyond” the geometric progression (for which the rational function is constant), they were termed hypergeometric from the ancient Greek prefix ˊυ′περ (“hyper”).
Why is the hypergeometric distribution called so?
What are the assumptions of hypergeometric distribution?
The following assumptions and rules apply to use the Hypergeometric Distribution: Discrete distribution. Population, N, is finite and a known value. Two outcomes – call them SUCCESS (S) and FAILURE (F).
How do you know if a distribution is hypergeometric?
The hypergeometric distribution is defined by 3 parameters: population size, event count in population, and sample size. For example, you receive one special order shipment of 500 labels. Suppose that 2% of the labels are defective. The event count in the population is 10 (0.02 * 500).