Applies ToSharePoint Server 订阅版 SharePoint Server 2019 SharePoint Server 2016 SharePoint Server 2013 SharePoint Server 2013 企业版 Microsoft 365 中的 SharePoint SharePoint Foundation 2010 SharePoint Server 2010 Microsoft 365 小型企业版中的 SharePoint Windows SharePoint Services 3.0

Returns the individual term binomial distribution probability. Use BINOMDIST in problems with a fixed number of tests or trials, when the outcomes of any trial are only success or failure, when trials are independent, and when the probability of success is constant throughout the experiment. For example, BINOMDIST can calculate the probability that two of the next three babies born are male.

Syntax

BINOMDIST(number_s,trials,probability_s,cumulative)

Number_s     is the number of successes in trials.

Trials     is the number of independent trials.

Probability_s     is the probability of success on each trial.

Cumulative     is a logical value that determines the form of the function. If cumulative is TRUE, then BINOMDIST returns the cumulative distribution function, which is the probability that there are at most number_s successes; if FALSE, it returns the probability mass function, which is the probability that there are exactly number_s successes.

Remarks

  • Number_s and trials are truncated to integers.

  • If number_s, trials, or probability_s is nonnumeric, BINOMDIST returns the #VALUE! error value.

  • If number_s < 0 or number_s > trials, BINOMDIST returns the #NUM! error value.

  • If probability_s < 0 or probability_s > 1, BINOMDIST returns the #NUM! error value.

  • The binomial probability mass function is:

    Equation

    where:

    Equation

    is COMBIN(n,x).

    Note: The COMBIN function is used here to illustrate the mathematical formula used by the BINOMDIST function. It is not a function that you can use in a list.

    The cumulative binomial distribution is:

    Equation

Example

Number_s

Trials

Probability_s

Formula

Description (Result)

6

10

0.5

=BINOMDIST([number_s],[trials],[probability_s],FALSE)

Probability of exactly 6 of 10 trials being successful (0.205078)

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