muteria.statistics

Basic statistics module.

This module provides functions for calculating statistics of data, including averages, variance, and standard deviation.

Calculating averages

Function	Description
mean	Arithmetic mean (average) of data.
fmean	Fast, floating point arithmetic mean.
geometric_mean	Geometric mean of data.
harmonic_mean	Harmonic mean of data.
median	Median (middle value) of data.
median_low	Low median of data.
median_high	High median of data.
median_grouped	Median, or 50th percentile, of grouped data.
mode	Mode (most common value) of data.
multimode	List of modes (most common values of data).
quantiles	Divide data into intervals with equal probability.

Calculate the arithmetic mean (“the average”) of data:

>>> mean([-1.0, 2.5, 3.25, 5.75])
2.625

Calculate the standard median of discrete data:

>>> median([2, 3, 4, 5])
3.5

Calculate the median, or 50th percentile, of data grouped into class intervals centred on the data values provided. E.g. if your data points are rounded to the nearest whole number:

>>> median_grouped([2, 2, 3, 3, 3, 4])  
2.8333333333...

This should be interpreted in this way: you have two data points in the class interval 1.5-2.5, three data points in the class interval 2.5-3.5, and one in the class interval 3.5-4.5. The median of these data points is 2.8333…

Calculating variability or spread

Function	Description
pvariance	Population variance of data.
variance	Sample variance of data.
pstdev	Population standard deviation of data.
stdev	Sample standard deviation of data.

Calculate the standard deviation of sample data:

>>> stdev([2.5, 3.25, 5.5, 11.25, 11.75])  
4.38961843444...

If you have previously calculated the mean, you can pass it as the optional second argument to the four “spread” functions to avoid recalculating it:

>>> data = [1, 2, 2, 4, 4, 4, 5, 6]
>>> mu = mean(data)
>>> pvariance(data, mu)
2.5

Exceptions

A single exception is defined: StatisticsError is a subclass of ValueError.