Application Guide

Poisson Pdf (poissPdf())
Computes a probability at x for the discrete Poisson distribution with the specified
mean, μ, which must be a real number >0. x can be an integer or a list of integers.
The probability density function (pdf) is:
This distribution is useful in determining the probability of obtaining a certain number
of successes before a trial begins. For example, you could use this calculation to
predict the number of heads that would occur in eight tosses of a coin.
Poisson Cdf (poissCdf())
Computes a cumulative probability for the discrete Poisson distribution with specified
mean, x.
This distribution is useful in determining the probability that a certain number of
successes occur between the upper and lower bounds of a trial. For example, you could
use this calculation to predict the number of heads displayed between coin toss #3 and
toss #8.
Geometric Pdf (geomPdf())
Computes a probability at x, the number of the trial on which the first success occurs,
for the discrete geometric distribution with the specified probability of success p. 0{p
{1 must be true. x can be an integer or a list of integers. The probability density
function (pdf) is:
This distribution is useful in determining the likeliest number of trials before a success
is obtained. For example, you could use this calculation to predict the number of coin
tosses that would be made before a heads resulted.
Geometric Cdf (geomCdf())
Computes a cumulative geometric probability from lowBound to upBound with the
specified probability of success, p.
This distribution is useful in determining the probability associated with the first
success occurring during trials 1 through n. For example, you could use this calculation
to determine the probability that heads display on toss #1, #2, #3, ..., #n.
Lists&Spreadsheet Application 335