Author: Sally Caldwell
I can remember that, as an undergraduate, I found it far too easy to fall into the trap of just trying to remember the steps needed to analyse data, and trusted the computer program without truly understanding the underlying principles. Statistics Unplugged is ideal for students who are starting to learn about statistics and want a solid grounding in the conceptual framework before moving on to the use of programs. It gives a clear explanation of the main formulae but it does not overwhelm readers with detailed maths. Its main focus is to make clear the underlying principles of statistics so that interpretation of results is clearer.
It is also a handy guide for those teaching the subject; a useful template on how to cover the fundamentals
The first chapter is devoted to a thorough grounding in the fundamentals, such as levels of measurement, populations and samples. It then moves on to describing the data, discussing measures, central tendency and dispersion. Chapters 3 and 4 focus on the shape of distributions and how this relates to data, and then discusses the impact this has on the distribution of real-world data. Chapter 5 sets out four fundamental concepts: random sampling, sampling error, sampling distribution of sample means and the central limit theorem. After setting out these principles, the book describes confidence intervals in chapter 6 and revisits Z scoring, which was introduced in chapter 4. Hypothesis testing is covered in chapters 7, 8 and 9 with special attention paid to an explanation of the meaning of the null hypothesis. The final chapters show students how to calculate the main statistical tests they will encounter that look at differences and relationships in data (for example, Anova, regression and chi square).
Throughout the book there are handy little fact-check boxes to test knowledge and there are end-of-chapter problems to solve, so student readers can be confident that they are ready to move on to the next section. The description of the key principles is simple to follow using easy-to-understand (if rather dull) examples. Statistics Unplugged is also a handy guide for those teaching the subject; it is a useful template on how to cover the fundamentals. I am sure that most students will outgrow this textbook quickly, but it provides a solid foundation in what can be a daunting subject and would be a sound starting point before having to deal with the complexities of computer programs. That said, students will still need to get to grips with programs, so I would recommend using this as a supplement to a more comprehensive core book, such as Andy Field’s Discovering Statistics Using… series, which also covers how to analyse data in programs.