Statistical Analysis of Spatial Point Patterns

intervals and statistical tests for one and two proportions. After building experience in the context of proportions, the reader can apply confidence intervals and tests to inference for one and two means and extend inference into linear models later in the book and course. Despite the comprehensive and rich selection of material, including multiple regression diagnostics and logistic regression, the authors could have spent more time on statistical power. The content on power is limited to narrative and exercises about the meaning of power, including understanding how power changes with changes in significance level and sample size. I believe that the authors could have taken the reader further by addressing power more explicitly in a variety of testing contexts and computational exercises (taking advantage of available technology, of course). Many of the examples and exercises are based on referenced real examples. In other situations the contexts seem trite; at least one exercise refers to a fictitious university called “Watsamatta U.” The authors make clear in the preface that their goal is to make the content accessible to the reader by incorporating humor throughout, but at times they seem to have taken this a little too far. The examples and exercises span a wide and relevant variety of contexts. It might have been helpful if a system of labels, icons, or color coding had been used to categorize exercises, such as “health science,” “physical science,” “agriculture,” and so on. The technology tips at the ends of the chapters are easy to find, allowing the book to be used with various software and graphing calculators even without specific external supplements. Naturally the book comes with a full complement of supporting materials for both the instructor and student, including ActivStats and an Excel Add-In called DDXL on a CD–ROM, datasets in many different formats on the Web site, and interesting generic course management software through the publisher. This book contains things I have never seen in other introductory statistics textbooks, such as the first names of Bonferroni, Venn, and Likert, and a photograph of George Gallup. The authors have obviously paid attention to the smallest details, and everything in the book, including the frequent use of humor and informal, conversational language, seems to have a purpose. Stats: Data and Models offers a relatively comprehensive and definitely readable extended first look at statistics at the undergraduate level. Teachers of two-semester statistics sequences or researchers and professionals looking for an accessible yet dense overview of statistics would be well served by this text.