People in general are curiously bad at estimating risks or chances – the mere existence of casinos, betting shops and national lotteries demonstrates this. Part of the problem is that so many of us are actively put off by the sight of numbers rather than words. Most people will understand the words “a one in ten chance” quite easily, but will start to get confused by a figure as simple as “10 per cent”. Many readers’ eyes just glaze over when faced with anything more complex. One glance at the algebraic formulae and occasional Greek squiggles that litter every entry in this book will lose the attention of 99 per cent of the population. This is extremely unfortunate. A basic understanding of probability – an ability to weigh up uncertainty, chance, luck or likelihood – is essential for navigating one’s way through life. Our lives are increasingly controlled by ever more complex algorithms; we ought to try to understand them.
I am very pleased to see a reference book that actually says what it is talking about. I seem to have looked at far too many specialised dictionaries which never actually provide a brief definition of their own subject. This book defines probability as a term “of uncertainty about some event's occurrence, or about the truth of some statement; in either case it may be used in a broad everyday sense, or used more narrowly to denote a formalization of the concept”. Though the book, thus, defines both senses, it largely concentrates on the formalization of the subject. This is a specialised reference text on the application of advanced mathematical statistics, not a general reader’s guide.
Because an understanding of statistics is so very important, and because so many people are put off by the sight of numbers, there are an enormous number of statistical reference books available. The Guide to Information Sources in Mathematics and Statistics (Tucker anderson, 2004), which was reviewed in this journal (RR 2005/372), listed a number of useful reference tools. Since the publication of that guide, we have reviewed, for example, the new edition of the Dictionary of Statistics (Upton and Cook, 2014) which our reviewer recommended to “students at school or university who are discovering mathematical statistics for the first time” (RR 2014/264) and the fourth edition of the Cambridge Dictionary of Statistics (Everitt and Skrondal, 2011) (RR 2011/224). I reviewed the American Psychological Association’s APA Dictionary of Statistics and Research Methods (Zedeck, 2014) (RR 2014/163), noting that an understanding of statistical methods is essential for psychologists, perhaps more than for any other science; yet psychology tends to be seen as a “soft science” and, therefore, recruits students who concentrated on the humanities at school and often share the general aversion to numbers. They need all the encouragement they can get – every new reference tool is welcome. I consulted an expert statistician – Brian Everitt, the emeritus professor of biometrics at the Institute of Psychiatry – who unblushingly recommended the Cambridge Dictionary of Statistics as absolutely the very best reference source on the topic, but a quick search through the back files of Reference Reviews pulled up recommendations of another half-dozen or so recent statistical reference tools which our reviewers found useful.
This book is the only dictionary specifically devoted to mathematical probability that I know of. The subject is, however, so intertwined with statistics that a large proportion of the terms in it are covered by statistical dictionaries. Applications of probability are also covered in reference tools relating to finance or insurance, operations research, risk management or game theory, so relevant terms are likely to be defined in dictionaries relating to those subjects. There is a distinct probability that general reference libraries or undergraduate-level academic libraries will find they already have access to adequate definitions of most of the 3,000 odd terms here. This book is, therefore, likely to appeal to a fairly limited market of university libraries catering for more advanced academic work in statistics, applied mathematics or operations research.
All libraries, catering for practically any age group (the younger they start the better) or for any subject interest, ought to have some guides to the interpretation of probability and statistics. For public library users, there are quite a range of inexpensive basic texts, such as Grimmett and Welsh (2014) or Brooks (2015) (I have not seen the latter yet, but it bears the imprimatur of the New Scientist which sounds promising), as well as the inevitable very short introductions (Haigh, 2012) and “for dummies” (Rumsey, 2006). This particular book is clearly aimed at a very small group of specialised readers who will find it to be a useful source of brief, dense, highly technical one-paragraph definitions, all of which, as far as I am aware, are accurate and relevant. All the entries have a single reference to a source of further reading, to encourage students to delve further into the topic.
