# math.stats #

## fn absdev #

``fn absdev<T>(data []T) T``

Measure of Dispersion / Spread Mean Absolute Deviation of the given input array Based on https://en.wikipedia.org/wiki/Average_absolute_deviation

## fn absdev_mean #

``fn absdev_mean<T>(data []T, mean T) T``

Measure of Dispersion / Spread Mean Absolute Deviation of the given input array Based on https://en.wikipedia.org/wiki/Average_absolute_deviation

## fn covariance #

``fn covariance<T>(data1 []T, data2 []T) T``

## fn covariance_mean #

``fn covariance_mean<T>(data1 []T, data2 []T, mean1 T, mean2 T) T``

Compute the covariance of a dataset using the recurrence relation

## fn freq #

``fn freq<T>(data []T, val T) int``

Measure of Occurance Frequency of a given number Based on https://www.mathsisfun.com/data/frequency-distribution.html

## fn geometric_mean #

``fn geometric_mean<T>(data []T) T``

Measure of Central Tendancy Geometric Mean of the given input array Based on https://www.mathsisfun.com/numbers/geometric-mean.html

## fn harmonic_mean #

``fn harmonic_mean<T>(data []T) T``

Measure of Central Tendancy Harmonic Mean of the given input array Based on https://www.mathsisfun.com/numbers/harmonic-mean.html

## fn kurtosis #

``fn kurtosis<T>(data []T) T``

## fn kurtosis_mean_stddev #

``fn kurtosis_mean_stddev<T>(data []T, mean T, sd T) T``

Takes a dataset and finds the kurtosis using the fourth moment the deviations, normalized by the sd

## fn lag1_autocorrelation #

``fn lag1_autocorrelation<T>(data []T) T``

## fn lag1_autocorrelation_mean #

``fn lag1_autocorrelation_mean<T>(data []T, mean T) T``

Compute the lag-1 autocorrelation of a dataset using the recurrence relation

## fn max #

``fn max<T>(data []T) T``

Maximum of the given input array

## fn max_index #

``fn max_index<T>(data []T) int``

Maximum of the given input array

## fn mean #

``fn mean<T>(data []T) T``

Measure of Central Tendancy Mean of the given input array Based on https://www.mathsisfun.com/data/central-measures.html

## fn median #

``fn median<T>(sorted_data []T) T``

Measure of Central Tendancy Median of the given input array ( input array is assumed to be sorted ) Based on https://www.mathsisfun.com/data/central-measures.html

## fn min #

``fn min<T>(data []T) T``

Minimum of the given input array

## fn min_index #

``fn min_index<T>(data []T) int``

Minimum of the given input array

## fn minmax #

``fn minmax<T>(data []T) (T, T)``

Minimum and maximum of the given input array

## fn minmax_index #

``fn minmax_index<T>(data []T) (int, int)``

Minimum and maximum of the given input array

## fn mode #

``fn mode<T>(data []T) T``

Measure of Central Tendancy Mode of the given input array Based on https://www.mathsisfun.com/data/central-measures.html

## fn population_stddev #

``fn population_stddev<T>(data []T) T``

Measure of Dispersion / Spread Population Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn population_stddev_mean #

``fn population_stddev_mean<T>(data []T, mean T) T``

Measure of Dispersion / Spread Population Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn population_variance #

``fn population_variance<T>(data []T) T``

Measure of Dispersion / Spread Population Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn population_variance_mean #

``fn population_variance_mean<T>(data []T, mean T) T``

Measure of Dispersion / Spread Population Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn quantile #

``fn quantile<T>(sorted_data []T, f T) T``

## fn range #

``fn range<T>(data []T) T``

Measure of Dispersion / Spread Range ( Maximum - Minimum ) of the given input array Based on https://www.mathsisfun.com/data/range.html

## fn rms #

``fn rms<T>(data []T) T``

Root Mean Square of the given input array Based on https://en.wikipedia.org/wiki/Root_mean_square

## fn sample_stddev #

``fn sample_stddev<T>(data []T) T``

Measure of Dispersion / Spread Sample Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn sample_stddev_mean #

``fn sample_stddev_mean<T>(data []T, mean T) T``

Measure of Dispersion / Spread Sample Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn sample_variance #

``fn sample_variance<T>(data []T) T``

Measure of Dispersion / Spread Sample Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn sample_variance_mean #

``fn sample_variance_mean<T>(data []T, mean T) T``

Measure of Dispersion / Spread Sample Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

## fn skew #

``fn skew<T>(data []T) T``

## fn skew_mean_stddev #

``fn skew_mean_stddev<T>(data []T, mean T, sd T) T``

## fn tss #

``fn tss<T>(data []T) T``

Sum of squares

## fn tss_mean #

``fn tss_mean<T>(data []T, mean T) T``

Sum of squares about the mean