The stats module contains statistical functions:
stats.binomialCDF()
The stats.binomialCDF() function evaluates the probability of getting fewer than or exactly
successes out of
trials in a binomial distribution with success probability
.
and
must be positive real integers.
must be a real number in the range
.
stats.binomialPDF()
The stats.binomialPDF() function evaluates the probability of getting
successes out of
trials in a binomial distribution with success probability
.
and
must be positive real integers.
must be a real number in the range
.
stats.chisqCDF()
The stats.chisqCDF() function returns the cumulative probability density at
in a
-squared distribution with
degrees of freedom.
must be a positive real dimensionless integer.
must be a positive real dimensionless number.
stats.chisqCDFi()
The stats.chisqCDFi() function returns the point
at which the cumulative probability density in a
-squared distribution with
degrees of freedom is
.
must be a positive real dimensionless integer.
must be a real number in the range
.
stats.chisqPDF()
The stats.chisqPDF() function returns the probability density at
in a
-squared distribution with
degrees of freedom.
must be a positive real dimensionless integer.
must be a positive real dimensionless number.
stats.gaussianCDF()
The stats.gaussianCDF() function evaluates the Gaussian cumulative distribution function of standard deviation
at
. The distribution is centred upon
.
and
must both be real, but may have any physical dimensions so long as they match.
stats.gaussianCDFi()
The stats.gaussianCDFi() function evaluates the inverse Gaussian cumulative distribution function of standard deviation
at
. The distribution is centred upon
.
and
must both be real, but may have any physical dimensions so long as they match.
stats.gaussianPDF()
The stats.gaussianPDF() function evaluates the Gaussian probability density function of standard deviation
at
. The distribution is centred upon
.
and
must both be real, but may have any physical dimensions so long as they match.
stats.lognormalCDF()
The stats.lognormalCDF() function evaluates the log normal cumulative distribution function of standard deviation
, centred upon
, at
.
must be real, positive and dimensionless.
and
must both be real, but may have any physical dimensions so long as they match.
stats.lognormalCDFi()
The stats.lognormalCDFi() function evaluates the inverse log normal cumulative distribution function of standard deviation
, centred upon
, at
.
must be real, positive and dimensionless.
and
must both be real, but may have any physical dimensions so long as they match.
stats.lognormalPDF()
The stats.lognormalPDF() function evaluates the log normal probability density function of standard deviation
, centred upon
, at
.
must be real, positive and dimensionless.
and
must both be real, but may have any physical dimensions so long as they match.
stats.poissonCDF()
The stats.poissonCDF() function returns the probability of getting
from a Poisson distribution with mean
, where
must be real, positive and dimensionless and
must be real and dimensionless.
stats.poissonPDF()
The stats.poissonPDF() function returns the probability of getting
from a Poisson distribution with mean
, where
must be real, positive and dimensionless and
must be a real dimensionless integer.
stats.tdistCDF()
The stats.tdistCDF() function returns the cumulative probability density at
in a
-distribution with
degrees of freedom.
must be a positive real dimensionless integer.
must be a positive real dimensionless number.
stats.tdistCDFi()
The stats.tdistCDFi() function returns the point
at which the cumulative probability density in a
-distribution with
degrees of freedom is
.
must be a positive real dimensionless integer.
must be a real number in the range
.
stats.tdistPDF()
The stats.tdistPDF() function returns the probability density at
in a
-distribution with
degrees of freedom.
must be a positive real dimensionless integer.
must be a positive real dimensionless number.