Difference between revisions of "Functions for descriptive statistics"
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+ | Descriptive statistics aim at characterising empirical data by summative parameters (and also by tables and plots}. | ||
+ | |||
+ | == Standard functions defined in math unit == | ||
+ | |||
The unit [[doc:rtl/math/index.html|math]] of the [[RTL]] provides a plethora of routines for descriptive statistics. | The unit [[doc:rtl/math/index.html|math]] of the [[RTL]] provides a plethora of routines for descriptive statistics. | ||
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* [[doc:rtl/math/sum.html| sum]]: Returns the sum of values of an array. | * [[doc:rtl/math/sum.html| sum]]: Returns the sum of values of an array. | ||
* [[doc:rtl/math/sumsandsquares.html| sumsandsquares]]: Returns sum and sum of squares of the values in an array. | * [[doc:rtl/math/sumsandsquares.html| sumsandsquares]]: Returns sum and sum of squares of the values in an array. | ||
+ | |||
+ | == Other 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: | ||
+ | |||
+ | <syntaxhighlight> | ||
+ | function sem(const data: array of Extended): real; | ||
+ | begin | ||
+ | sem := stddev(data) / sqrt(length(data)); | ||
+ | end; | ||
+ | </syntaxhighlight> | ||
+ | |||
[[Category:Statistical algorithms]] | [[Category:Statistical algorithms]] |
Revision as of 16:07, 2 January 2015
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 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 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.
Other 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;