Discovering Statistics Using IBM SPSS Statistics
by Andy Field
Andy Field's widely used SPSS textbook turns a dry subject into a readable, funny course, with step-by-step software guidance that rarely leaves beginners stranded.
What It's About
This is a large, course-length textbook covering the statistics usually taught in psychology, social science, and related degrees. It starts with the basics of research design, measurement, and descriptive statistics, then works through t-tests, ANOVA, correlation, regression, factor analysis, and multilevel modelling. The defining feature is the voice. Field writes in a chatty, joke-heavy style, and his examples are deliberately odd, on the theory that a ridiculous scenario is easier to remember than a dull one.
Each technique comes with step-by-step instructions for IBM SPSS Statistics, including menu paths, screenshots, and guidance on reading the output, so you can follow along with your own data. This edition adds a maths diagnostic tool, a redesigned layout, a revamped digital resource with datasets and video, and new material on replication, open science, and Bayesian thinking.
Reading it feels like working through a long, friendly course rather than dipping into a reference. Chapters build on one another, and the book assumes little prior maths while still explaining the logic behind the methods. It is long and sometimes repetitive, but it is one of the few statistics books that leaves many readers feeling capable rather than defeated.
Read this if you…
- want a full, self-paced statistics course for a psychology, social science, or dissertation project
- prefer working in SPSS and need screenshots and output interpretation alongside the theory
- find conventional statistics textbooks impossible to finish and want a funny companion through the material
Skip it if you…
- want a concise reference you can dip into quickly without reading through a long narrative
- need statistics for a field that does not use SPSS, or want to learn R or Python coding instead
Key Ideas
- 1
Choosing a method from the question
The book frames each test around a research question and the type of data you have. The aim is to teach you how to select an appropriate analysis, not just how to run one, which matters most when you are writing a dissertation and nobody has told you which test to use.
- 2
Many tests as one underlying model
Field repeatedly shows that t-tests, ANOVA, and regression are variations on the same linear framework. Seeing this connection makes later chapters easier, because a new technique often looks like a familiar idea with an extra variable or a different error assumption.
- 3
Software as part of the learning
SPSS walkthroughs are integrated with the statistics, not tacked on at the end. You learn to set up the analysis, read the output tables, and write up results in the style journals expect. Some readers will find the screenshots reassuring, while others will find them dated as menus change between versions.
- 4
Humour as a memory aid
The jokes and absurd examples are not just decoration. Field uses them to make abstract ideas stick, so a silly scenario can help you recall what a p-value or an interaction effect actually means weeks later. Whether this works depends heavily on whether you find the style charming or irritating.
- 5
Newer concerns in this edition
Replication, open science, and Bayesian thinking have been added to reflect debates about reproducibility in psychology and beyond. These sections introduce the ideas and their rationale, though they are an introduction rather than a full treatment of Bayesian methods.
Limitations
The book is long, and its breadth means some advanced topics get less depth than specialists would like. The humour and the often sexual or silly examples are not to everyone's taste, and some readers find the constant jokes tiring over hundreds of pages. Because it is tied to specific SPSS versions, the step-by-step screenshots and menu paths will drift as the software changes. Those who want rigorous mathematical derivations will need to look elsewhere.
Questions Readers Ask
- Is this book good for complete beginners?
- Yes, if you are starting from little or no maths. The early chapters explain basic concepts gently and the SPSS instructions are detailed. The sheer length and the range of later topics can overwhelm some newcomers, so it helps to read at a steady pace and use the companion materials for practice datasets.
- How does it compare to Discovering Statistics Using R?
- The content is largely the same, but the software differs. The SPSS version suits readers using point-and-click menus, while the R version teaches coding. If your course or dissertation uses SPSS, choose this one. If you are learning R or want to build programming skills, the R edition is the better fit.
- Is it still relevant with so many newer tools available?
- For the core methods, yes. Regression, ANOVA, and factor analysis have not changed, and the book explains the reasoning behind them rather than just button presses. Newer tools and software versions do change the practical steps, so check the current edition and supporting materials before following the menus exactly.
- Published
- 2018
- ISBN
- 9781526419521
- Difficulty
- intermediate
- Category
- SPSS for Windows
Book details and cover from Google Books.
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