Functions for descriptive statistics
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Revision as of 23:49, 11 January 2015 by Jwdietrich (talk | contribs) (→Standard functions defined in math unit)
Descriptive statistics aim at characterising empirical data by summative parameters (and also by tables and plots}.
Standard functions defined in math unit
The unit math of the RTL provides a plethora of routines for descriptive statistics.
mean
: Returns the mean value of an array.stddev
: Returns the (sample) standard deviation of an array.popnstddev
: Returns the (population) standard deviation of an array.meanandstddev
: Returns mean and standard deviation of an array.momentskewkurtosis
: Returns the first four moments of an array.variance
: Returns the (sample) variance of an array.popnvariance
: Returns the (population) variance of an array.totalvariance
: Returns the total variance of an array.sumofsquares
: Returns the sum of squares of an array.sum
: Returns the sum of values of an array.sumsandsquares
: Returns sum and sum of squares of the values in an array.
These functions expect an array of predefined length (e.g. array[1..100] of float
) or a 0-based open array (e.g. array of extended
) with subsequent call of the SetLength
procedure.
Standard functions defined in other units
- length: Delivers the length (n) of an array.
Custom functions
Standard error of the mean
The standard error of the mean (SEM) is a measure that estimates how precisely the true mean of the population can be known.
Calculation of SEM is simple:
function sem(const data: array of Extended): real;
begin
sem := stddev(data) / sqrt(length(data));
end;