Discovering Statistics and Data

This is the third edition of an introduction to statistics and data analysis. It is a part of a package available from the publisher that includes a companion website with datasets and options for courseware, an eBook, and bundling with Minitab, SPSS, or JMP software. This review addresses only the textbook..

The book is designed for an introductory course for students from a variety of disciplines and requires very little prior background in mathematics. Probably basic algebra with brief exposure to the exponential function would be sufficient. Mostly students need to be able to understand and apply formulas. With more computationally intensive questions, students would likely be expected to use appropriate software tools from Minitab, SPSS, or the like.

The topics covered are standard; they begin with introductory material on the nature of statistics and data analysis and move through descriptive statistics, basic probability and standard probability distributions to sampling, hypothesis testing, statistical inference and both simple and multiple regression. The book concludes with treatments of analysis of variation and some discussion of non-parametric tests.

The author has clearly tried to do everything possible to make the book appealing to students. The pace is very deliberate, with plenty of examples and a multitude of exercises. The book is laid out on large pages with big margins and color is used extensively. It is probably about a third longer than most comparable texts. Part of this is because of the larger number of examples and exercises, and probably at least as much is due to the extra graphics, frequent sidebars and more expansive layout. For example, one whole page is given to a composite photograph showing images of each one of a sequence of 42 coin flips, each accompanied by the cumulative frequency of heads appearing. As an example, it’s not a bad idea — just maybe a bit overelaborate.

This new edition includes some additional material following recommendations from the Guidelines for Assessment in Statistical Education (GAISE). This includes an improved and more careful treatment of hypothesis testing and the addition of a number of “concept” exercises designed to test a student’s basic comprehension.

One of the more notable features of the book is the unusually extensive introduction. The author takes pains to make the subject look interesting and valuable to students who might need some extra motivation. The occasional sidebars probably help in this respect, with short biographies, a bit of history and the occasional amusing digression. This would be a good text for students who might have some reluctance to study statistics and is probably best suited to average students. Stronger students might find the pace too slow.

The review copy I received is identified as an annotated instructor’s edition. It’s hard to say what “annotated” means, but as far as I can tell this involves only a preface aimed at instructors and an answer key for all the exercises.

Bill Satzer (bsatzer@gmail.com) was a senior intellectual property scientist at 3M Company. His training is in dynamical systems and particularly celestial mechanics; his current interests are broadly in applied mathematics and the teaching of mathematics.