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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 Peter Farrell
Profile icon Peter Farrell
Alvaro Fuentes Alvaro Fuentes
Profile icon Alvaro Fuentes
Ajinkya Sudhir Kolhe Ajinkya Sudhir Kolhe
Profile icon Ajinkya Sudhir Kolhe
Quan Nguyen Quan Nguyen
Profile icon Quan Nguyen
Alexander Joseph Sarver Alexander Joseph Sarver
Profile icon Alexander Joseph Sarver
Marios Tsatsos Marios Tsatsos
Profile icon 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

Data Preparation

All applied statistics starts with a dataset and a problem to solve. In the real world, we never do statistical analysis in a vacuum; there is always a business problem to solve, a topic that needs to be quantitatively understood, or a scientific question to ask. Understanding the problem is always the very first step of any statistical analysis. The second step is to collect and prepare the data. Data collection is not a topic of this book, so we will go directly into data preparation. Therefore, before diving into doing some statistical calculations, we need to make sure we understand our business problem and that we have prepared our dataset.

Introducing the Dataset

In this subsection, we will introduce the dataset we will use in this chapter and perform some basic data preparation tasks. Knowing the dataset will give you a bit more context when we define the business problem.

We are going to use the strategy games dataset, which contains real-world information...

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