Statistics (scipy.stats)#
In this tutorial, we discuss many, but certainly not all, features of
scipy.stats. The intention here is to provide a user with a
working knowledge of this package. We refer to the
reference manual for further details.
Note: This documentation is work in progress.
- Probability distributions
- Continuous Statistical Distributions
- Discrete Statistical Distributions
- Getting help
- Common methods
- Random number generation
- Shifting and scaling
- Shape parameters
- Freezing a distribution
- Broadcasting
- Specific points for discrete distributions
- Fitting distributions
- Performance issues and cautionary remarks
- Remaining issues
- Building specific distributions
- Sample statistics and hypothesis tests
- Universal Non-Uniform Random Number Sampling in SciPy
- Kernel density estimation
- Multiscale Graph Correlation (MGC)
- Quasi-Monte Carlo