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The aim of Statistics for evidence-based practice and evaluation is “to introduce statistics to undergraduate and graduate students in the helping professions.” The statistical methods are presented from first basis, and the intended audience for the book is very broad.
From the start, Rubin gives a good argument for the use of statistics and why anyone in the helping professions requires some basic knowledge. All chapters have lengthy explanations of the reasons for using the different statistical tools as well as long descriptions of the tools themselves. At the end of each chapter there are InfoTrac exercises. These exercises use information from resources in the internet (such as primary research papers), which should encourage the reader to examine articles critically. The downside is that possibly not everyone will have an internet connection.
The emphasis is on explaining statistical methods through text, which results in a smaller number of graphs, formulas, and tables than other texts in this area. The quality of the information is variable. For example, the discussion of the different uses of the mean, median, and mode as location parameters is helpful, whereas the discussion on normal distributions (chapter 7) is incorrect, because the distributions referred to are bell shaped and symmetrical (not all of them follow a normal distribution).
In general, there is an oversimplification in many areas of the book with formulas not adequately described and calculations not clearly explained. To be fair to Rubin, a book describing all the caveats for the use of the statistical tests mentioned would be at least twice the size of this one.
The book comprises 3 parts: (1) introduction and data management, (2) descriptive statistics, and (3) inferential statistics. Part 1 gives a good description of how to prepare data for the analysis. This issue is often overlooked in most textbooks and is a crucial part of all statistical analysis. Part 2 explains the basic statistical measures and the use of graphs for the presentation of data. Part 3 describes the usual statistical methods used in research: hypothesis testing, ANOVA, regression, etc.
This book will be useful to people who know little about statistical methods and who prefer word explanations to graphs or figures. The examples are relatively limited, and the layout (2 columns per page) is clearly designed for text. Users and/or readers of statistics with a moderate understanding of the methods will probably find it difficult to follow the descriptions or to use it as a reference book.