16 Sep

# Statistical Tools – Te Grotenhuis and Van der Weegen (2009)

How does one teach statistics? Is it more important to start with mathematical thoroughness, or to help students to gain a conceptual understanding first? Few give a comprehensive introduction to statistics for those without the otherwise indispensable mathematical background. Manfred te Grotenhuis and Theo van der Weegen recently published an introductory book on statistics, explaining statistical concepts using words and graphs, rather than formulas.

Less than a year ago, I wrote these exact words. I then discussed the publication of a Dutch book on statistics, to which I provided minor assistance. Now, I repeat these words to introduce the Enligsh translation of this conceptual introduction to statistics, called Statistical Tools. Again, I contributed to this publication, this time by providing a first, rough, translation from Dutch to English. Let me repeat below what I wrote before on this blog, for of course this still holds relevance for the translation to English:

With the focus on practical application rather than statistical theory, the first chapter starts explaining the goal of inferential statistics, meanwhile introducing the concepts of measurement and variables. Considerable attention is paid to the importance of high quality data to perform your analyses on. The second chapter deals with descriptive statistics, both in a numerical and a graphical way. Here, also the concepts of a distribution and of correlation are introduced. The third and final chapter discusses the testing of hypotheses, using techniques as the cross-table, tests for means and proportions, various forms of correlation, and finally multiple regression.

Clearly, the setup of this book is what one might expect from an introduction to statistics. However, I think this book has a unique approach by its strong focus on the conceptual level, rather than the (mathematical) statistical theory. Nevertheless, it does not shy away from relatively complex subjects such as the multiple regression. Even on the conceptual level, it pays a lot of attention to the assumptions required for the various analyses discussed. The practical approach of this book is enhanced even further, because all examples come from â€˜real lifeâ€™ research. On the accompanying website SPSS data files and syntax files are made available, so that every example from the book can be repeated by the reader.

Aimed at the novice statistics student, this book offers a comprehensible and conceptual approach at statistics. It will surely help students of statistics to grasp what theyâ€™re actually doing when pushing SPSSâ€™s buttons or trying to interpret published figures. In that sense, I think that for many statistics student, this book successfully reaches is goal of transforming statistics form an abstract undertaking to an actually useful and applicable tool.

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This post is part of my ‘Reading List’. In this series I jot down some thoughts about the books I read and enjoyed. Some posts my give a somewhat balanced overview of a book, others will just focus on some aspects that, for whatever reason, caught my attention. Never are these posts meant as an evaluation or even review of the book. I just like to share some impressions.

An overview of my Reading List is available, which contains both a list of the books that I wrote about, and another list of books I’m planning to read.