Caring enough to learn to deal with hypothesis testing?

Statistics and nursing are traditionally not easy bedfellows, so a statistics textbook aimed at nurses is a welcome addition to the body of research knowledge for both clinical nurses and nurse researchers. Statistics have recently taken on a prominence with the advent of evidence-based practice. Applying evidence-based research findings requires nurses to be able to understand and interpret fundamental statistical concepts such as hypothesis testing and significance. John Maltby et al's textbook covers these concepts and, more importantly, explains them clearly using a minimum of mathematics.

This book gets round presenting statistical equations and their related technicalities by using datasets with examples taken from the Statistical Package for the Social Sciences (SPSS). These are in an easy-to-understand format, using the topic coverage of selected chapters as a sequential development for manipulating the common features of SPSS, from the basics such as labelling variables to more advanced techniques such as running inferential statistical tests.

This application of SPSS, embedded within an accompanying explanation of how and why to use statistics, will be particularly appealing to postgraduate nursing students undertaking quantitative research dissertations or theses.

Furthermore, the book is clearly signposted, with the first chapter setting the scene for a consideration of the scope of statistical inquiry alongside a notated introduction to the succeeding chapters. According to the preface, the book is aimed at pre-registration students as well as qualified nurses undertaking post-registration courses. But many nursing programmes do not include study of statistics until the post-registration level, so the usefulness of this book for student nurses must be questioned.

All of the authors are psychologists. This is a boon in one respect because owing to the history of their subject they have an intimate knowledge of the nature of statistics. Accordingly, they are often able to explain complex statistical ideas clearly to other professionals with a minimum of academic posturing, as is reflected in this textbook. However, Maltby et al's work could have benefited from some greater nursing input, as statistics from one important and developing area have been neglected: evidence-based practice. Increasingly, nurses in their everyday clinical practice need to have a working knowledge of the meaning of applied statistical terms such as intention-to-treat analysis, the number needed to treat and relative risk reduction. A consideration of some of these applied statistical concepts would have given a greater appeal and critical depth to an otherwise jargon-free, practical presentation of using statistics.

Who is it for? Postgraduate nursing students and clinical nurses seeking to conduct quantitative research or interpret the findings of statistical studies.

Presentation - A clearly structured format using SPSS and clinical case scenarios to provide examples and explanations of statistical concepts.

Would you recommend it? Yes, this book will be on the new reading list for my applying research to practice unit.