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  • Installing
  • User Guide
  • API reference
  • Building from source
  • Development
  • Release notes
  • GitHub
  • Twitter

Section Navigation

User guide

  • Special functions (scipy.special)
  • Integration (scipy.integrate)
  • Optimization (scipy.optimize)
  • Interpolation (scipy.interpolate)
  • Fourier Transforms (scipy.fft)
  • Signal Processing (scipy.signal)
  • Linear Algebra (scipy.linalg)
  • Sparse Arrays (scipy.sparse)
  • Sparse eigenvalue problems with ARPACK
  • Compressed Sparse Graph Routines (scipy.sparse.csgraph)
  • Spatial data structures and algorithms (scipy.spatial)
  • Statistics (scipy.stats)
    • Probability distributions
    • Sample statistics and hypothesis tests
    • Universal Non-Uniform Random Number Sampling in SciPy
    • Kernel density estimation
    • Multiscale Graph Correlation (MGC)
    • Quasi-Monte Carlo
  • Multidimensional image processing (scipy.ndimage)
  • File IO (scipy.io)
  • SciPy User Guide
  • Statistics (scipy.stats)
  • Sample...

Sample statistics and hypothesis tests#

  • Analysing one sample
  • Comparing two samples
  • Resampling and Monte Carlo Methods

Statistical hypothesis tests are used to decide whether data sufficiently support a particular hypothesis. SciPy defines a number of hypothesis tests, listed in Hypothesis Tests and related functions. You can find examples to each test in the corresponding docstring.

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Yule-Simon Distribution

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Analysing one sample

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