Book Image

NumPy: Beginner's Guide

By : Ivan Idris
Book Image

NumPy: Beginner's Guide

By: Ivan Idris

Overview of this book

Table of Contents (21 chapters)
NumPy Beginner's Guide Third Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
NumPy Functions' References
Index

Time for action – analyzing random values


We will generate random values that mimic a normal distribution and analyze the generated data with statistical functions from the scipy.stats package.

  1. Generate random values from a normal distribution using the scipy.stats package:

    generated = stats.norm.rvs(size=900)
  2. Fit the generated values to a normal distribution. This basically gives the mean and standard deviation of the dataset:

    print("Mean", "Std", stats.norm.fit(generated))

    The mean and standard deviation appear as follows:

    Mean Std (0.0071293257063200707, 0.95537708218972528)
    
  3. Skewness tells us how skewed (asymmetric) a probability distribution is (see http://en.wikipedia.org/wiki/Skewness). Perform a skewness test. This test returns two values. The second value is the p-value—the probability that the skewness of the dataset does not correspond to a normal distribution.

    Note

    Generally speaking, the p-value is the probability of an outcome different than what was expected given the null hypothesis...