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The Statistics and Calculus with Python Workshop

You're reading from The Statistics and Calculus with Python Workshop

Product type Book

Published in Aug 2020

Publisher Packt

ISBN-13 9781800209763

Pages 740 pages

Edition 1st Edition

Languages

Concepts

Authors (6):

Peter Farrell

Alvaro Fuentes

Ajinkya Sudhir Kolhe

Quan Nguyen

Alexander Joseph Sarver

Marios Tsatsos

View More author details

Table of Contents (14) Chapters

Preface

1. Fundamentals of Python

2. Python's Main Tools for Statistics

3. Python's Statistical Toolbox

4. Functions and Algebra with Python

5. More Mathematics with Python

6. Matrices and Markov Chains with Python

7. Doing Basic Statistics with Python

8. Foundational Probability Concepts and Their Applications

9. Intermediate Statistics with Python

10. Foundational Calculus with Python

11. More Calculus with Python

12. Intermediate Calculus with Python

Appendix

8. Foundational Probability Concepts and Their Applications

Overview

By the end of this chapter, you will be familiar with basic and foundational concepts in probability theory. You'll learn how to use NumPy and SciPy modules to perform simulations and solve problems by calculating probabilities using simulations. This chapter also covers how to calculate the probabilities of events using simulations and theoretical probability distributions. Along with this, we'll conceptually define and use random variables included in the scipy.stats module. We will also understand the main characteristics of the normal distribution and calculate probabilities by computing the area under the curve of the probability distribution.

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Authors (6)

Peter Farrell

Peter Farrell learned to program from the Logo code in Seymour Paperts Mindstorms. A student introduced him to Python and he never looked back. In 2015, he self-published Hacking Math Class with Python on applying Python programming to learning and teaching high-school math. In 2019, No Starch Press published his second book, Math Adventures with Python. In his books, he also presents 21st-century topics, such as Cellular Automata, 3D Graphics, and Genetic Algorithms. Currently, he teaches Python and Math in the Dallas, Texas area.

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Alvaro Fuentes

Alvaro Fuentes is a senior data scientist with a background in applied mathematics and economics. He has more than 14 years of experience in various analytical roles and is an analytics consultant at one of the ‘Big Three' global management consulting firms, leading advanced analytics projects in different industries like banking, technology, and consumer goods. Alvaro is also an author and trainer in analytics and data science and has published courses and books, such as 'Become a Python Data Analyst' and 'Hands-On Predictive Analytics with Python'. He has also taught data science and related topics to thousands of students both on-site and online through different platforms such as Springboard, Simplilearn, Udemy, and BSG Institute, among others.

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Ajinkya Sudhir Kolhe

Ajinkya Sudhir Kolhe is a programmer working for a tech company in the Bay area. He holds a M.S. in Computer Science and has experience in the tech industry of 5+ years. His area of interests include problem solving, analytics and applications in Python.

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Quan Nguyen

Quan Nguyen, the author of the first edition of this book, is a Python programmer with a strong passion for machine learning. He holds a dual degree in mathematics and computer science, with a minor in philosophy, earned from DePauw University. Quan is deeply involved in the Python community and has authored multiple Python books, contributing to the Python Software Foundation and regularly sharing insights on DataScience portal. He is currently pursuing a Ph.D. in computer science at Washington University in St. Louis.

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Alexander Joseph Sarver

Alexander Joseph Sarver is an ambitious data scientist and content creator with 6 years of mathematical teaching experience.

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Marios Tsatsos

Marios Tsatsos has 8+ years of experience in research in Physics, analytical thinking, modeling, problem solving and decision making.

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