Review: Interpreting Quantitative Data with IBM SPSS Statistics (2ed), by Rachad Antonius, SAGE Publications, 2013

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    Liia L
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    Book review

    Interpreting Quantitative Data with IBM SPSS Statistics (2ed), by Rachad Antonius, SAGE Publications, 2013, xxviii+343pp

    The book Interpreting Quantitative Data with IBM SPSS Statistics, by Prof. Rachad Antonius, is highly relevant for the students starting to use SPSS, as no prior knowledge of the SPSS is required, but also for the ones who want to brush up their skills and knowledge. Like the author himself states, the “book is addressed to students taking a first course in quantitative methods for the social sciences, and to researchers who are writing a dissertation or a research report, and who have to use quantitative data at an elementary or intermediate level” (p xxii). The benefit of the book is twofold. From the one hand, it introduces the technical aspects of the SPSS, on the other hand, it helps to interpret the data and use it in a research project, while avoiding the most common pitfalls.

    When it comes to the structure of the book, the book is divided into five parts (plus appendices): introduction to quantitative methods, descriptive statistics, methodological tools, inferential statistics, and statistical association. Each part is further divided into 2-3 chapters. Owing to the brief contents, more detailed table of contents, and index, it is easy for a reader to find in the book exactly the section which helps him the most with his current research or problem. “The book deals with the production, presentation, analysis, and interpretation of quantitative data” (p. xxii) in a systematic way. In the beginning of every chapter is a checklist on the content of the chapter. In the end of the chapters are exercises and a tutorial. The book is rich in illustrative figures, tables, and examples, and accompanied by a website. In the very end of the book is a glossary with the main terms covered in the book.

    It is the 2nd edition and compared to the first edition, the difference is significant. The structure has been reshuffled and some new topics/chapters have been added (e.g. one-way and two-way ANOVA, linear regression).

    The book has a pedagogic character. It is addressed to both an instructor and a student. An added value of the book compared to some other reference books on SPSS is exactly that in addition to on how to manipulate the SPSS, it also gives guidance on how to use the data in a research project and what to keep in mind. It sees the SPSS as a part of the social research process and therefore focuses in addition to the data production/manipulation also on the analysis and interpretation of quantitative data. And also on the very basics of a research project (e.g. research object and research question, literature review, hypothesis). Therefore the book is recommended already in the very beginning of the designing the research. For the reader who needs additional information, there are in the end of each chapter also suggestions for further reading.

    In conclusion, the book is certainly a beneficial companion for becoming familiar with SPSS and using the data computed with the SPSS in a research project. As the book is written by assuming a student has no previous experience in SPSS or statistics (p. xxii), the text is simple and easy to follow.

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