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Applying Math with Python

You're reading from Applying Math with Python

Product type Book

Published in Jul 2020

Publisher Packt

ISBN-13 9781838989750

Pages 358 pages

Edition 1st Edition

Languages

Concepts

Mathematical Programming

Author (1):

Sam Morley

Table of Contents (12) Chapters

Preface

1. Basic Packages, Functions, and Concepts

2. Mathematical Plotting with Matplotlib

3. Calculus and Differential Equations

4. Working with Randomness and Probability

5. Working with Trees and Networks

6. Working with Data and Statistics

7. Regression and Forecasting

8. Geometric Problems

9. Finding Optimal Solutions

10. Miscellaneous Topics

11. Other Books You May Enjoy

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Further reading

There are a large number of textbooks on statistics and statistical theory. The following book was used as reference for this chapter:

Mendenhall, W., Beaver, R., and Beaver, B., (2006), Introduction To Probability And Statistics, 12th ed., (Belmont, Calif.: Thomson Brooks/Cole)

The pandas documentation (https://pandas.pydata.org/docs/index.html) and the following pandas book serve as good references for working with pandas:

McKinney, W.,(2017),Python for Data Analysis, 2nd ed.,(Sebastopol: O'Reilly Media, Inc, US)

The SciPy documentation (https://docs.scipy.org/doc/scipy/reference/tutorial/stats.html) also contains detailed information about the statistics module that was used several times in this chapter.

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Authors (1)

Sam Morley

Sam Morley is an experienced lecturer in mathematics and a researcher in pure mathematics. He is currently a research software engineer at the University of Oxford working on the DataSig project. He was previously a lecturer in mathematics at the University of East Anglia and Nottingham Trent University. His research interests lie in functional analysis, especially Banach algebras. Sam has a firm commitment to providing high-quality, inclusive, and enjoyable teaching, with the aim of inspiring his students and spreading his enthusiasm for mathematics.

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