Computes the discrete inverse cumulative distribution function (CDF), or the value x such that the probability that the random variate X, where X describes the selected distribution type, takes on a value less than or equal to it is cdf(x). You must manually select the polymorphic instance to use.


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Inputs/Outputs

  • cdbl.png cdf(x) —

    cdf(x) is the cumulative probability Prob[X ≤ x].

  • ci32.png M —

    M is the number of elements in the population.

  • ci32.png k —

    k is the number of successes in the population.

  • ci32.png n —

    n is the number of items drawn without replacement.

  • ii32.png x —

    x is the number of successes out of the sample of n items drawn from the population.

  • ii32.png error —

    error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.

    • When using the Bernoulli instance of the VI, X represents a Bernoulli-distributed variate with one of two possible outcomes: success (x = 1) or failure (x = 0). The Bernoulli probability parameter p is the probability of success of a single trial or experiment.

    Examples

    Refer to the following example files included with LabVIEW.

    • labview\examples\Mathematics\Probability and Statistics\Display Discrete Probability Distributions.vi