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F Pdf ( F Pdf())
Computes the probability density function (pdf) for the F distribution at a
specified x value. numerator df (degrees of freedom) and denominator df
must be integers >0. The probability density function (pdf) is:
where
n = numerator degrees of freedom
d = denominator degrees of freedom
This distribution is useful in determining the probability that two samples have
the same variance. The draw option is available when F Pdf is invoked from a
formula cell.
F Cdf ( F Cdf())
Computes the F distribution probability between lowBound and upBound for
the specified dfnumer (degrees of freedom) and dfDenom. You can click the
Draw (Shade area) check box to shade the area between the lower and upper
bounds. Changes to the initial lowBound and upBound automatically update
the distribution.
This distribution is useful in determining the probability that a single
observation falls within the range between the lower bound and upper bound.
Binomial Pdf (binomPdf())
Computes a probability at x for the discrete binomial distribution with the
specified numtrials and probability of success ( p ) on each trial. The x
parameter can be an integer or a list of integers. 0{ p {1 must be true. numtrials
must be an integer >0. If you do not specify x, a list of probabilities from 0 to
numtrials is returned. The probability density function (pdf) is:
where n = numtrials
This distribution is useful in determining the probability of success in a
success/failure trial, at trial n . For example, you could use this distribution to
predict the probability of getting heads in a coin toss on the fifth toss.
Binomial Cdf (binomCdf())
Computes a cumulative probability for the discrete binomial distribution with n
number of trials and probability p of success on each trial.
Lists&Spreadsheet Application 343