Statistic
accumulateState
Accumulates the state flags of all cells in a tensor
DPMO
returns the defects per million opportunities (DPMO) for the given specification limits and distribution or the given number of trials and number of failures. The 7parameters are USL, LSL, trials, failures, distribution (0=normal), and up to 3 parameters describing the distribution.

LSL: is the lower specification limit.

USL: is the upper specification limit

trials: is the number of trials. May be empty if a distribution is provided.

failures: is the number of failures. May be empty if a distribution is provided. Must be >4 if no distribution is provided.

dist: Describes the distribution. May be empty if no distribution is provided. Normal distribution = 1.

param1: is the 1st parameter of the distribution (mean or shape)

param2: is the 2nd parameter of the distribution (standard deviation or scale)

param3: is the 3rd parameter of the distribution, if defined.
FisherTest
Performs the Fisher Test
geoMean
Calculates the geometric mean of a sample or population. The geometric mean is the nth root of the product of n values. In can be used e.g. to calculate a medium growth rate.
geoMeanExist
Calculates the geometric mean of a sample or population. Evaluates only existing relations in a matrix. Does not count empty cells.
harMean
Calculates the harmonic mean of a sample or population. The harmonic mean is the inverse of the sum of inverses of the values.
harMeanExist
Calculates the harmonic mean of a sample or population. Evaluates only existing relations in a matrix. Does not count empty cells.
identical
detects identical rows or columns in a matrix or tensor.
max
Returns the largest number in a container.
maxExist
Returns the largest existing number in a container. If the container or its respective row or column is empty, a default response is returned.
mean
Calculates the mean of a sample or population. The mean is the arithmetic average of a group of values.
meanExist
Calculates the mean of a sample or population. Evaluates only existing relations in a matrix. Does not count empty cells.
median
Calculates the median. Data from n samples is ordered from smallest to largest. For an odd sample size, median is the ordered value at (n+1)/2, for an even sample size median is the mean of the 2 middle ordered values.
medianExist
Calculates the median. Evaluates only existing relations in a matrix. Does not count empty cells.
min
Returns the smallest number in a container.
minExist
Returns the smallest existing number in a container. If the container or its respective row or column is empty, a default response is returned.
NChooseK
calculates the binomial coefficient (n choose k).
normdist
Returns the normal cumulative distribution for the specified mean and standard deviation. This function has a very wide range of applications in statistics, including hypothesis testing.

x: is a probability corresponding to the normal distribution

m: is the arithmetic mean of the distribution.

s: is the standard deviation of the distribution
normdistinv
Returns the inverse of the normal cumulative distribution (i.e. the z value) for the specified mean, standard deviation, and percentage.

x: is a probability corresponding to the normal distribution

m: is the arithmetic mean of the distribution.

s: is the standard deviation of the distribution
quartile
Calculates the quartiles. Data from n samples is ordered from smallest to largest. The first quartile is the value at n/4, the third quartile is the value at 3 n/4.

x: is the region with the sample or population for which the quartile is to be determined.

quartile: is the quartile to be returned. This argument must be one of 0,1,2,3,4. If set to 1, the first quartile is returned. If set to 3, the third quartile is returned. 0,2 and 4 return the lowest value, the median and the highest value.
quartileExist
Calculates the quartiles. Evaluates only existing relations in a matrix. Does not count empty cells.

x: is the region with the sample or population for which the quartile is to be determined.

quartile: is the quartile to be returned. This argument must be one of 0,1,2,3,4. If set to 1, the first quartile is returned. If set to 3, the third quartile is returned. 0,2 and 4 return the lowest value, the median and the highest value.
rootDiffSquares
Calculates the square root of a²b². If (a²b²) is negative, the function returns 0
rootSumSquares
Calculates the square root of a²+b²
size
returns the size (colums or rows) of an object

x: is the vector, matrix or tensor

dim: is either the index of the dimension (0..n) or the tree of the dimension.
snormdist
Returns the standard normal cumulative distribution function, i.e. the area under the curve for a given value of z. The distribution has a mean of 0 (zero) and a standard deviation of one.
snormdistinv
Returns the inverse of the standard normal cumulative distribution (i.e. the z value for a given percentage). The distribution has a mean of zero and a standard deviation of one.
stdDev
Calculates the standard deviation of a sample.
stdDevExist
Calculates the standard deviation of a sample. Evaluates only existing relations in a matrix. Does not count empty cells.
stdDevP
Calculates the standard deviation of a population, when all data is available.
stdDevPExist
Calculates the standard deviation of a population, when all data is available. Evaluates only existing relations in a matrix. Does not count empty cells.
stdErrorMean
Calculates the standard error of mean, defined as the standard deviation of the sample divided through the square root of the sample size.
stdErrorMeanExist
Calculates the standard error of mean. Evaluates only existing relations in a matrix. Does not count empty cells.
trimmedMean
Calculates the trimmed mean of a sample or population.

x: is the region with the sample or population for which the trimmed mean is to be determined.

percent: is the percentage of both largest and smallest values to be removed before calculating the mean. For the trimmed mean, this value should be set to 5%. When set to 0, the normal mena is returned.
trimmedMeanExist
Calculates the trimmed mean of a sample or population. Evaluates only existing relations in a matrix. Does not count empty cells.

x: is the region with the sample or population for which the trimmed mean is to be determined.

percent: is the percentage of both largest and smallest values to be removed before calculating the mean. For the trimmed mean, this value should be set to 5%. When set to 0, the normal mena is returned.
var
Calculates the variance of a sample.
varExist
Calculates the variance of a sample. Evaluates only existing relations in a matrix. Does not count empty cells.
varP
Calculates the variance of a population, when all data is available.
varPExist
Calculates the variance of a population, when all data is available. Evaluates only existing relations in a matrix. Does not count empty cells.
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