For those who want to further their skills and knowledge, the authors provide exercises based on the data tables, as well as a list of references. An understanding of the modeling technique is developed through examples, using JMP Pro and the data tables provided with the book. For those readers who want a glimpse of the mechanics behind a technique, a section called 'Looking Inside the Black Box' discusses the methodology behind the algorithm, providing appropriate statistical detail. Each modeling chapter captures the reader's attention with three short sections: A section where the topic is mentioned 'In the News', a section listing typical business problems where the technique applies, and a section showcasing the expected outcome of the modeling technique. 'What sets the book apart, though, is its elegant structure. Data sets accompany the book so that a reader can easily follow along. Part 4 of the book covers more advanced methods that require JMP Pro, including JMP's bootstrap forest and boosted tree methods, boosted neural nets, penalized (generalized) regression methods, cross validation, and model comparison techniques. Most of this material requires only JMP software. Part 3 of the book covers multiple linear regression, logistic regression, decision trees, and neural networks. The book is comprehensive, covering a wide array of modeling techniques. 'Building Better Models with JMP Pro provides a clean and concise introduction to the topic of modeling using JMP Pro. Building Better Models with JMP(R) Pro Book Reviews Building Better Models with JMP Pro

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