Interpreting Quantitative Data with IBM SPSS Statistics (Student review)

February 28, 2013

Author: Rachad Antonius
Edition: Second
Publisher: Sage
Pages: 376
Price: £85.00 and £29.99
ISBN: 9781446207420 and 07437

Tackling statistics can be a daunting prospect for many students. Nevertheless, at some stage in their degree most social science students will be required to produce, analyse and interpret statistical data. The difficulty of getting to grips with the software most commonly used by undergraduates, IBM SPSS (Statistical Package for the Social Sciences), can be greatly lessened with a detailed step-by-step aid. Rachad Antonius’ Interpreting Quantitative Data with IBM SPSS Statistics is a good option.

The difficulty of getting to grips with IBM SPSS can be greatly lessened with a detailed step-by-step aid

The text introduces the reader to the basic language used in, and the basic concepts of, statistics and quantitative methods. It addresses the production, presentation, analysis and interpretation of quantitative data by providing explanations of the procedures used to compute statistical results, but importantly also details how such statistical results are to be interpreted. Whereas some texts make assumptions about readers’ familiarity with statistical terminology and processes, Antonius assumes no prior knowledge of IBM SPSS software or of statistics in general, which makes this text a must-have for statistics novices.

Via an end-of-chapter tutorial accompanying each topic, Antonius guides the reader through the individual functions of SPSS, ensuring that the information covered in each chapter can be effectively put into practice.

A list of further reading concludes each chapter, allowing the reader to enhance their understanding and newly acquired knowledge, if desired.

Whereas some texts make assumptions about the reader’s familiarity with statistical terminology and processes, Antonius assumes no prior knowledge

SPSS screen shots placed throughout the text will be useful in guiding the reader through instructed procedures, ensuring that each step of the process is conducted correctly. Figures, tables and graphs are also supplied, helping to illustrate how output should look and how data should be reported.

This second edition has been updated to include new chapters on one-way and two-way Anova, the chi-square test and linear regression, sets of exercises and “real-life” examples to aid learning, keywords for each chapter to support revision and a companion website with answers to the exercises, along with additional data sets and PowerPoint slides for further practice.

Interpreting Quantitative Data with IBM SPSS Statistics is clearly written and easy to navigate. For more advanced statisticians, or students taking advanced statistic modules, more in-depth texts will be required. However, as noted by the author, the book is intended as an introductory first course in quantitative methods, and for its intended audience I believe this book will prove to be of great value.

Who is it for?
Undergraduate social science students and novice statisticians.

Presentation:
Clear structure and good use of illustrations.

Would you recommend it?
Highly.

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