expyriment.misc.statistics

The statistics module.

This module contains miscellaneous stastistical functions for expyriment.

Attributes

Modules

Classes

Functions

expyriment.misc.statistics.frequence_table(data)

Returns the frequency table of the data as dictionary.

Parameters:

data : list

list of numerical data

Returns:

out : dict

dict.keys : values, dict.values : frequencies

expyriment.misc.statistics.mean(data)

Returns the mean of data.

Parameters:

data : list

list of numerical data

Returns:

out : float or None

Notes

The function ignores all non-numerical elements in the data and returns None if no numerical element has been found. In contrast to standard math and numpy functions, this function is robust against type violations.

expyriment.misc.statistics.median(data)

Returns the median of data.

Parameters:

data : list

list of numerical data

Returns:

out : float or None

Notes

The function ignores all non-numerical elements in the data and returns None if no numerical element has been found. In contrast to standard math and numpy functions, this function is robust against type violations.

expyriment.misc.statistics.mode(data)

Returns the mode, that is, the most frequent value in data.

Parameters:

data : list

list of numerical data

Returns:

out : float or None

expyriment.misc.statistics.std(data)

Returns the standard deviation of data.

Parameters:

data : list

list of numerical data

Returns:

out : float or None

Notes

The function ignores all non-numerical elements in the data and returns None if no numerical element has been found. In contrast to standard math and numpy functions, this function is robust against type violations.

expyriment.misc.statistics.variance(data)

Returns the variance of data.

Parameters:

data : list

list of numerical data

Returns:

out : float or None

Notes

The function ignores all non-numerical elements in the data and returns None if no numerical element has been found. In contrast to standard math and numpy functions, this function is robust against type violations.