Thomas Nield

Grokking Statistics

"An excellent, playful introduction to foundational statistical ideas and calculations."
—Matthew Housley, Co-author of Fundamentals of Data Engineering

Grokking Statistics makes the core ideas of statistics intuitive, practical, and surprisingly entertaining. Using relatable examples, illustrations, and clear explanations, Thomas Nield shows you how to reason about uncertainty, draw useful conclusions from data, and recognize when the numbers themselves may be misleading. You’ll learn to move beyond deterministic thinking and develop the skeptical, questioning mindset that good statistical analysis requires.

Starting with the relationship between samples and populations, you’ll build a practical understanding of probability distributions, the normal distribution, the central limit theorem, confidence intervals, hypothesis testing, and linear and logistic regression. Along the way, you’ll apply these ideas to examples ranging from manufacturing tolerances and business decisions to tornado data and toddler meltdowns. Python handles the calculations so you can concentrate on what the results mean and when you should trust them.

Just as importantly, Grokking Statistics teaches you to question data itself. You’ll learn to look for biased samples, questionable assumptions, misleading metrics, overfitting, p-hacking, and other ways statistical reasoning can go wrong. These are essential practical skills. They matter whether you’re evaluating a research finding, analyzing business data, building a software product, or assessing the performance of a machine learning model.

Clear Python examples explain the concepts throughout the book. Thomas’s practical, sometimes whimsical approach keeps the focus on understanding rather than memorizing formulas. Reviewer Mark J. Miller of Route.com says, “With practical, entertaining examples, you’ll learn key principles and skills that will level up your BS detector!” Reviewer Thomas Briegel of Plaurag Edelmetalle GmbH calls it an “accessible and practical introduction to statistics that avoids intimidating math.”

True to the promise of “grokking,” this book brings your understanding of statistics to a point deep enough to use confidently—and to know how to question conclusions drawn from data. You’ll come away ready to make smarter decisions under uncertainty, evaluate claims critically, and put statistical thinking to work wherever data is involved.

Real-World Workflows with ChatGPT

Step into the world of AI-powered problem solving. In this hands-on series of liveProjects, you will play the role of a librarian, an investigative journalist, and a data analyst—all with ChatGPT as your AI assistant. First, you will spark community discussion by creating engaging content around a classic American short story. Then, you will analyze a real NTSB report from a self-driving car accident, uncovering possible causes with the help of ChatGPT. Finally, you will work as a data analyst, using ChatGPT’s Python capabilities to explore a bird strike dataset from the FAA. Along the way, you will learn practical AI productivity techniques, integrate multimodal workflows, and develop the ability to use ChatGPT to enhance your thinking and decision-making.

What Causes Bird Strikes

In this liveProject, you will act as a researcher investigating the causes of bird strikes in the aviation industry. You will work with a dataset and limited context, using ChatGPT to explore the data, generate insights, and guide your analysis. You will use ChatGPT to generate Python code, perform analysis, and challenge your assumptions to avoid bias. The project concludes with a structured summary of findings and exporting your data into a queryable SQL database.

Analyzing an Accident Report

In this liveProject, you will use ChatGPT to investigate an in-depth report of a self-driving car accident. You will acquire the source material, upload it, and use ChatGPT to generate and refine hypotheses about why the accident occurred. You will incorporate external context to deepen your analysis, turning vague questions into structured insights and expanding your research beyond a single document.

The Legend of Sleepy Hollow

In this liveProject, you will take on the role of a librarian using generative AI tools like ChatGPT to support a research project. You will develop effective prompts to analyze whether The Legend of Sleepy Hollow by Washington Irving is suitable for a new exhibition. After generating analysis with ChatGPT, you will extract relevant insights and use them to create engaging materials for the exhibition.