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# Module statistics

source code

Module for calculating simple statistics.

 Functions
list of lists of float
 bucket(values=None, lower=0.0, upper=200.0, inc=100, verbose=False) Generate a discrete probability distribution for the given values. source code
float
 gaussian(x=None, mu=0.0, sigma=1.0) Calculate the probability for a Gaussian probability distribution for a given x value. source code
float
 std(values=None, skip=None, dof=1) Calculate the standard deviation of the given values, skipping values if asked. source code
 Variables
__package__ = `'lib'`

Imports: exp, pi, sqrt

 Function Details

### bucket(values=None, lower=0.0, upper=200.0, inc=100, verbose=False)

source code

Generate a discrete probability distribution for the given values.

Parameters:
• `values` (list of float) - The list of values to convert.
• `lower` (float) - The lower bound of the distribution.
• `upper` (float) - The upper bound of the distribution.
• `inc` (int) - The number of discrete increments for the distribution between the lower and upper bounds.
• `verbose` (bool) - A flag which if True will enable printouts.
Returns: list of lists of float
The discrete probability distribution.

### gaussian(x=None, mu=0.0, sigma=1.0)

source code

Calculate the probability for a Gaussian probability distribution for a given x value.

Parameters:
• `x` (float) - The x value to calculate the probability for.
• `mu` (float) - The mean of the distribution.
• `sigma` (float) - The standard deviation of the distribution.
Returns: float
The probability corresponding to x.

### std(values=None, skip=None, dof=1)

source code

Calculate the standard deviation of the given values, skipping values if asked.

Parameters:
• `values` (list of float) - The list of values to calculate the standard deviation of.
• `skip` (list of bool or None.) - An optional list of booleans specifying if a value should be skipped. The length of this list must match the values. An element of True will cause the corresponding value to not be included in the calculation.
• `dof` (int) - The degrees of freedom, whereby the standard deviation is multipled by 1/(N - dof).
Returns: float
The standard deviation.

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