# WorksheetFunction.HypGeom_Dist Method (Excel)

Office 2010

Returns the hypergeometric distribution. HYPGEOM_DIST returns the probability of a given number of sample successes, given the sample size, population successes, and population size. Use HYPGEOM_DIST for problems with a finite population, where each observation is either a success or a failure, and where each subset of a given size is chosen with equal likelihood.

## Version Information

Version Added: Excel 2010

## Syntax

expression .HypGeom_Dist(Arg1, Arg2, Arg3, Arg4)

expression A variable that represents a WorksheetFunction object.

### Parameters

Name

Required/Optional

Data Type

Description

Arg1

Required

Double

Sample_s - the number of successes in the sample.

Arg2

Required

Double

Number_sample - the size of the sample.

Arg3

Required

Double

Population_s - the number of successes in the population.

Arg4

Required

Double

Number_population - the population size.

Arg5

Optional

Variant

Cumulative - a logical value that determines the form of the function. If cumulative is TRUE, then HYPGEOM_DIST returns the cumulative distribution function; if FALSE, it returns the probability mass function.

Double

## Remarks

• All arguments are truncated to integers.

• If any argument is nonnumeric, HYPGEOM_DIST returns the #VALUE! error value.

• If sample_s < 0 or sample_s is greater than the lesser of number_sample or population_s, HYPGEOM_DIST returns the #NUM! error value.

• If sample_s is less than the larger of 0 or (number_sample - number_population + population_s), HYPGEOM_DIST returns the #NUM! error value.

• If number_sample ≤ 0 or number_sample > number_population, HYPGEOM_DIST returns the #NUM! error value.

• If population_s ≤ 0 or population_s > number_population, HYPGEOM_DIST returns the #NUM! error value.

• If number_population ≤ 0, HYPGEOM_DIST returns the #NUM! error value.

• The equation for the hypergeometric distribution is: where: x = sample_s n = number_sample M = population_s N = number_population HYPGEOM_DIST is used in sampling without replacement from a finite population.

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