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We are better off when our decisions are guided by evidence and reason but working with data can be tricky. Data can behave in ways that violate our intuition and expectations. It's easy to be fooled.

Downey's ability to explain complex concepts in a simple and easy-to-understand way is truly remarkable. Downey draws on a wide range of case studies to illustrate the principles of statistical thinking encouraging readers to question assumptions and be wary of misleading statistics. He debunks common statistical fallacies and teaches readers how to avoid falling into traps that can lead to misinterpretations and bad decisions.

All of the code the author used to do the analysis and generate the figures is now available online (allendowney.github.io/ProbablyOverthinkingIt/intro.html), which is just perfect.

You really can't go wrong with Sorokin.

Great, as expected.

A great book whose brilliance, as so many of King's novels, lies in its exploration of the complex interplay between the supernatural and the psychological.

The Overlook's evil influence is both tangible and intangible, blurring the lines between reality and hallucination. Jack's descent into madness, fueled by alcoholism, repressed anger, and the hotel's sinister influence, is both terrifying and relatable, as we witness the gradual unraveling of a man teetering on the brink of insanity.

And the ending is terrific.

Julia For Data Analysis is a must-read for anyone who wants to learn how to use Julia for data science. It is suitable for beginners who want to get started with Julia, as well as for experienced data scientists who want to explore Julia's capabilities and features. The book is well-written, well-organized, and well-illustrated, making it a joy to read and learn from. I highly recommend this book to anyone who is interested in data analysis with Julia.

Terrible. So bad I still can't believe it.

I hope it's at least as good as the first one.