No Bullshit Guide to Statistics

No Bullshit Guide to Statistics#

The book#

The No Bullshit Guide to Statistics is now available to purchase via Gumroad: gum.co/noBSstats. This book introduces statistics in a rigorous, yet accessible manner. It is the result of seven years of research, writing, and editing by Ivan Savov and collaborators. Read the announcement blog post for more details about the book contents and the eBook prerelease in October 2025. If you want to learn stats, go and get it now.

Computational notebooks#

Use this binder button to run the notebooks interactively: Binder.

Good news; bad news#

The good news is that I’m going to teach you everything I know about statistics. This means I’ll show you all the formulas and computations required to understand statistics deeply. We’ll learn multiple alternative approaches for doing statistical calculations, including visualizations, math models, and Python code. By the end of this book, you’ll have developed practical skills for data management, analytical stills for doing probability calculations, and gained valuable experience with the various procedures in the statistics toolbox.

The bad news is that I’m going to teach you everything I know about statistics. This means there will be a lot of equations, and you’ll need to concentrate to understand fancy math expression like summations \(\Sigma_{i=1}^n x_i\) and integrals \(\int f_X(x) dx\). You have to trust me that the math complexity is necessary complexity, because knowing the math details will allow you to understand statistics better.

You’ll also have to become comfortable with code examples that illustrate statistical procedures expressed as Python commands. These code examples will keep us honest: if the answers we obtain using math formulas are the same as the answers we obtain by running the Python code, then we can be sure we’re doing things right. This is why these notebooks exist—so you can try things for yourself.

Contents