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Grokking Statistics
Not yet published
Expected 29 Sep 26Master probability, distributions, and hypothesis testing--and actually enjoy it! Author Thomas Nield delivers explanations, clever graphics, and everyday examples that make statistics approachable, memorable, and fun. Everything you need to know about statistics—skillfully illustrated and carefully explained.
In the real world, most decisions involve uncertainty. Statistical analysis reduces uncertainty by interpreting data, from setting product demand forecasts to predicting customer behaviors. With this book, you’ll build a strong foundation in statistical analysis by working through engaging mini projects that put each skill you learn into practice immediately.
In Grokking Statistics you will
• Understanding the shape of data with probability distributions
• Connect samples and populations with the central limit theorem
• Confidence intervals and hypothesis testing
• Machine learning basics including linear and logistic regression
• Spot fallacies, p-hacking, and incentive traps
About the book
Grokking Statistics takes you on a journey beyond mathematics into the fascinating world of probability, prediction, and “what-if” reasoning. You’ll learn the basics of statistics from the ground up as you explore tornado data from NOAA, model the perfect cup of coffee, and accurately test whether a potato chip bag is the size it claims. Written to be practical at every step, this book also takes on ethics and real-world pitfalls, so you can apply statistics responsibly. You’ll also learn how to express statistics in straightforward Python code.
About the reader
No prior knowledge of statistics needed. Examples use Python.
About the author
Thomas Nield is an instructor at University of Southern California and the founder of Nield Consulting Group and Yawman Flight.
In the real world, most decisions involve uncertainty. Statistical analysis reduces uncertainty by interpreting data, from setting product demand forecasts to predicting customer behaviors. With this book, you’ll build a strong foundation in statistical analysis by working through engaging mini projects that put each skill you learn into practice immediately.
In Grokking Statistics you will
• Understanding the shape of data with probability distributions
• Connect samples and populations with the central limit theorem
• Confidence intervals and hypothesis testing
• Machine learning basics including linear and logistic regression
• Spot fallacies, p-hacking, and incentive traps
About the book
Grokking Statistics takes you on a journey beyond mathematics into the fascinating world of probability, prediction, and “what-if” reasoning. You’ll learn the basics of statistics from the ground up as you explore tornado data from NOAA, model the perfect cup of coffee, and accurately test whether a potato chip bag is the size it claims. Written to be practical at every step, this book also takes on ethics and real-world pitfalls, so you can apply statistics responsibly. You’ll also learn how to express statistics in straightforward Python code.
About the reader
No prior knowledge of statistics needed. Examples use Python.
About the author
Thomas Nield is an instructor at University of Southern California and the founder of Nield Consulting Group and Yawman Flight.
Kindle Edition
Expected publication September 29, 2026
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Displaying 1 of 1 review
June 4, 2026
I had the pleasure of reading this through Manning’s excellent early access program, MEAP. Since I read an unpublished version of the book, please keep in mind that I have not read a single page of chapter 4, which I believe through context will be on the CLT and Law of Large Numbers.
I found this book to be a leisurely introduction or refresher on fundamental statistics. The final chapter is a surprisingly insightful and generalizable guide on how to navigate your career, which I found particularly helpful as I am very early in my career. If you enjoy reading about statistics, I would recommend, but do not expect a highly technical textbook. There are python examples for most of the concepts covered, for those interested in some practical applications.
I found this book to be a leisurely introduction or refresher on fundamental statistics. The final chapter is a surprisingly insightful and generalizable guide on how to navigate your career, which I found particularly helpful as I am very early in my career. If you enjoy reading about statistics, I would recommend, but do not expect a highly technical textbook. There are python examples for most of the concepts covered, for those interested in some practical applications.
Displaying 1 of 1 review