You're reading from Essential Statistics for Non-STEM Data Analysts Get to grips with the statistics and math knowledge needed to enter the world of data science with Python

Product type Paperback

Published in Nov 2020

Publisher Packt

ISBN-13 9781838984847

Length 392 pages

Edition 1st Edition

Languages

Python

Concepts

Data Science

Author (1):

Rongpeng Li

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Getting Started with Statistics for Data Science

2. Chapter 1: Fundamentals of Data Collection, Cleaning, and Preprocessing FREE CHAPTER

3. Chapter 2: Essential Statistics for Data Assessment

4. Chapter 3: Visualization with Statistical Graphs

5. Section 2: Essentials of Statistical Analysis

6. Chapter 4: Sampling and Inferential Statistics

7. Chapter 5: Common Probability Distributions

8. Chapter 6: Parametric Estimation

9. Chapter 7: Statistical Hypothesis Testing

10. Section 3: Statistics for Machine Learning

11. Chapter 8: Statistics for Regression

12. Chapter 9: Statistics for Classification

13. Chapter 10: Statistics for Tree-Based Methods

14. Chapter 11: Statistics for Ensemble Methods

15. Section 4: Appendix

16. Chapter 12: A Collection of Best Practices

17. Chapter 13: Exercises and Projects

18. Other Books You May Enjoy

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Avoiding the use of misleading graphs

Graphics convey much more information than words. Not everyone understands P-values or statistical arguments, but almost everyone can tell if one piece of a pie plot is larger than another piece of pie plot, or if two-line plots share a similar trend. However, there are many ways in which graphs can also damage the quality of a visualization or mislead readers.

In this section, we will examine two examples. Let's start with the first example – misleading graphs.

Example 1 – COVID-19 trend

The following graph is a screenshot taken in early April 2020. A news channel showed this graph of new COVID-19 cases per day in the United States. Do you spot anything strange?

Figure 12.2 – A screenshot of COVID-19 coverage of a news channel

The issue is on the y axis. If you look closely, the y axis tickers are not separated equally but in a strange pattern. For example, the space between 30 and 60...