During the chapter in hypothesis testing, he describes the most common methods to perform hypothesis testing to compare two different groups. In chapter 10, the author explains basic concepts necessary to understand regression like least square, residuals, goodness of fit and weighted resampling.
Then, in chapter 11 he describes multiple regression analysis, nonlinear relationships and logistic regression. Finally, he explains the more advanced subjects like time series and survival analysis.
Professor Downey is a senior engineer and a data scientist. Consequently, accuracy is part of his training, background, and career. This book is highly accurate. In the age of big data, this book is relevant and essential for any engineer that wants to move to the are of big data. The longevity of the book is unknown, the area is moving very fast, but he is teaching basic concepts, so I expect that the book will be relevant for at least a decade.
IMHO, the book is very clear for anybody with some background in computer science and programming. On the other hand, for somebody without any knowledge of Python or programming, it could be hard. The author explains in the preface that some experience in programming will be necessary to understand the book. The author has some other open text books like "Think Python" that should be read before reading this book. Consistency is to the extreme. Every chapter starts with an introduction, explanations of methods, examples, and description of the code used to demonstrate the concepts or to generate the graphics.
Also, the author provides code, exercises, and a glossary for every chapter. The book is modular in the sense that we can read sections that we are not familiar and skip parts that we are not familiar.
Every chapter has multiple sections with subheaders just to provide an example chapter 10 has seven different sub-sections plus the exercises and glossary. However, skipping sections or dividing parts among the various students could be confusing because the flow of the book requires understanding essential concepts before moving to more complex chapters.
Buy on Amazon. Book description If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. Show and hide more. Table of contents Product information. Exercises Glossary 6. ISBN: You might also like book Introduction to Probability by Joseph K. Downey 5. ISBN Your tags:. Send-to-Kindle or Email Please login to your account first Need help? Please read our short guide how to send a book to Kindle.
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