Roderick Little’s new book: Seminal Ideas and Controversies in Statistics

Around a year ago, Professor Rod Little asked me if I’d mind being on the cover of a book he was finishing along with Fisher, Neyman and some others (can you identify the others?). Mind?  The book is Seminal Ideas and Controversies in Statistics (Routledge, 2025), and it has been out about a month.  Little is the Richard D. Remington Distinguished University Professor of Biostatistics at the University of Michigan. Here’s the Preface:

Preface:

Statistics has developed as a field through seminal papers and fascinating  controversies. This book concerns a wide-ranging set of 15 statistical topics,  grouped into three sets:

Part I, Chapters 1–6. Philosophical approaches to statistical inference,

Part II, Chapters 7–12. Statistical methodology, and

Part III, Chapters 13–15. Topics on statistical design, focusing on the role  of randomization.

The chapters are grouped by topic and have some interconnections, but  they are also freestanding and do not need to be read in order.  In each chapter, I list one or more key papers on these topics and include as  other reading some later papers that may help to explain them. I then summarize the main ideas of these papers and give my personal perspective on  them. The goal is to expand readers knowledge on statistics literature and  encourage a historical perspective on the subject. I am not a historian, and  my goal is understanding rather than historical accuracy. I also acknowledge  my own limitations – I welcome hearing from readers who think the book  has it wrong. Proofs are avoided – the focus is on ideas, not mathematical  completeness – and simple examples are favored over generality.  The topics covered here have motivated my interest in statistics

The topics covered here have motivated my interest in statistics over my  career. They include what I consider the most important statistics paper in  the latter part of the 20th century (can you guess which one that is, after  reading the book?). Also, we all love controversies – who has not turned  to a contentious Royal Statistical Society discussion before reading the  main paper? The list is far from comprehensive, and others would have  undoubtedly chosen different topics, although I suspect there would be  some overlap.

This book is intended for individuals familiar with the main tools of statistics like multiple regression, repeated-measures analysis, basic properties of  distributions, and key asymptotic approaches such as maximum likelihood.  The target audience includes doctoral students in statistics and biostatistics,  and other statisticians who know the basics but are interested in the history  of statistics and would like to deepen their understanding of key ideas and  controversies.

When we teach a subject we generally say, “this is how to do it” without  much discussion of weaknesses or alternatives approaches. This book is different in that my purpose is to present the clash of ideas, and hence to sow  doubt and confusion about topics on the grounds that they may promote a deeper understanding. You will see I have a perspective on many of these  topics, but you don’t have to share the same views.

When taking coursework, students may not have read much of the original  literature in statistics journals. Most of the papers discussed here are well  written, if not always using modern-day English. Thus, I think reading the  set of papers is helpful to gaining an appreciation for how to write well on  statistics topics. This is particularly useful for students who will be writing  doctoral dissertations, but clear writing and communication skills are important in many careers that involve statistics. In the appendix, I offer some style  tips on how to write good statistical articles or other written communications  involving statistics.

Key aims of the book are:

• To cover and discuss a number of important ideas in the history of statistics, concerning (a) philosophical approaches, (b) seminal problems in statistical analysis, and (c) design topics, focusing on the role of randomization
• Provide a deeper understanding and appreciation of the history of statistics
• Discuss disagreements in the literature, which make for interesting reading
• Learn various aspects of statistics research by reading good examples in the literature
• Promote good English style in the presentation of statistical ideas by learning from papers that are well written. My own style tips on writing statistical papers are included as an Appendix.

Little, Roderick J. A.. Seminal Ideas and Controversies in Statistics (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) (p. xii).

Congratulations, Rod! And thanks so much for including my pic!