I am Professor of Philosophy of Science at the University of Bristol. I am interested in most areas of contemporary philosophy, in particular the interplay between philosophy and the natural and social sciences. Much of my recent work has focused on evolutionary biology, a science that is replete with implications for traditional philosophical debates about human nature, knowledge, and our place in the world.
This ambitious book, written by a distinguished philosopher, is a contribution to what might be called the “epistemology of evolutionary biology.” Sober starts by offering a general analysis of the concept of evidence based on probability theory, then applies this analysis to issues in the theory of evolution. He explains why the evidence favours evolution over the hypothesis of “intelligent design,” then tackles the thorny methodological problem of how to infer evolutionary history from observations on contemporary species. Though difficult, the book is clearly written and repays close study.
How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design are untestable; whether they are discredited by the fact that many adaptations are imperfect; how evidence bears on whether…
My primary interest is in brain function. Because the principal job of
the brain is to process information, it is necessary to define exactly
what information is. For that, there is no substitute for Claude
Shannon’s theory of information. This theory is not only quite
remarkable in its own right, but it is essential for telecoms,
computers, machine learning (and understanding brain function).
I have written ten "tutorial introduction" books, on topics which vary
from quantum mechanics to AI.
In a parallel universe, I am still an Associate Professor at the
University of Sheffield, England.
This is a more comprehensive and mathematically rigorous book than Pierce’s book. For the novice, it should be read-only after first reading Pierce’s more informal text. Due to its vintage, the layout is fairly cramped, but the content is impeccable. At almost 500 pages, it covers a huge amount of material. This was my main reference book on information theory for many years, but it now sits alongside more recent texts, like MacKay’s book (see below). It is also published by Dover, so it is reasonably priced.
Written for an engineering audience, this book has a threefold purpose: (1) to present elements of modern probability theory — discrete, continuous, and stochastic; (2) to present elements of information theory with emphasis on its basic roots in probability theory; and (3) to present elements of coding theory. The emphasis throughout the book is on such basic concepts as sets, the probability measure associated with sets, sample space, random variables, information measure, and capacity. These concepts proceed from set theory to probability theory and then to information and coding theories. No formal prerequisites are required other than the usual undergraduate…
Most of the one billion people with disabilities in the world are chronically unemployed. Years ago, I set out on a mission to research why that is, and to then attempt to prove that people with disabilities and others are not unemployed for lack of ability. I discovered that we all lack understanding regarding what they need in order to bring their considerable abilities to bare. Fifteen years ago, I founded CY, a for-profit company as a proving ground and showcase for the solutions I found. Over 1,500 employees, 5 weddings, and two court cases later – I have quite a story to tell.
We are primed to measure things against the yardstick of averages, judged according to how closely we come to it or how far we deviate from it. It affects our own self-confidence, how we view and grade our performance and worth.
The assumption that metrics comparing us to an average--like GPAs, personality test results, and performance review ratings--reveal something meaningful about our potential is so ingrained in our consciousness that we don't even question it. That assumption is spectacularly—and scientifically—wrong.
Together with great stories about the folly of averages (the one about pilot chairs really got me) and many research facts and stats it conveys a very important message about how we view the world.
'Must the tyranny of the group rule us from cradle to grave? Absolutely not, says Todd Rose in a subversive and readable introduction to what has been called the new science of the individual ... Readers will be moved' Abigail Zuger, The New York Times
'Groundbreaking ... The man who can teach you how not to be average' Anna Hart, Daily Telegraph
'Fascinating, engaging, and practical. The End of Average will help everyone - and I mean everyone - live up to their potential' Amy Cuddy, author of Presence
'Lively and entertaining ... a cheering story of how the square…
I am proud to be a human (social) scientist but think that we could collectively achieve a much more successful human science enterprise. And I believe that a better human science would translate into better public policy. Most human scientists focus on their own research, paying little attention to how the broader enterprise functions. I have written many works of a methodological nature over the years. I am pleased to point here to a handful of works with sound advice for enhancing the human science enterprise.
I really liked Williams’ writing style. He is very clear, provides good examples, and is very careful in his argumentation.
I very much liked – and indeed borrowed – his strategy of summarizing the main arguments of each chapter. This is especially important since his book addresses a wide range of challenges in social science. I especially liked his discussion of how the variables we measure are never perfect proxies for the phenomena that we hope to understand.
I also liked his careful discussion of how social scientists need to be more reflective in their work. And I found his discussion of the nature of causation in social science deeply insightful.
Realism and Complexity in Social Science is an argument for a new approach to investigating the social world, that of complex realism. Complex realism brings together a number of strands of thought, in scientific realism, complexity science, probability theory and social research methodology.
It proposes that the reality of the social world is that it is probabilistic, yet there exists enough invariance to make the discovery and explanation of social objects and causal mechanisms possible. This forms the basis for the development of a complex realist foundation for social research, that utilises a number of new and novel approaches to…
My father, when he consented to talk about all the moments in his life when the odds against his survival were so small as to make them statistically non-existent, would say, ‘I was lucky.’ Trying to understand what he meant got me started on this book. As well as being a novelist, I’m a poker player. Luck is a subject that every poker player has a relationship to; more importantly it’s a subject that every person has a relationship to. The combination of family history and intellectual curiosity and the gambler’s desire to win drove me on this quest.
Sadly, Games, Gods, and Gambling by FN David is out of print.This is the next best thing. Lorraine Daston has the supreme gift of making the complicated idea seem straightforward. This is an account of the frenzy for measuring that happened in the 18th century, and how it made the world we live in today, when the gambler’s eye for odds has become the algorithm of taming chance that guides all our decisions.
What did it mean to be reasonable in the Age of Reason? Classical probabilists from Jakob Bernouli through Pierre Simon Laplace intended their theory as an answer to this question--as "nothing more at bottom than good sense reduced to a calculus," in Laplace's words. In terms that can be easily grasped by nonmathematicians, Lorraine Daston demonstrates how this view profoundly shaped the internal development of probability theory and defined its applications.
I'm an executive coach, adjunct faculty at several top-tier business schools, and run a boutique firm consulting firm focused on organizational strategy solutions. My diverse and eclectic background in mergers & acquisitions, organization effectiveness, and strategy execution, coupled with two decades of experience in emerging markets in Asia, the Middle East, and North Africa, helps me grasp challenging people issues. I'm passionate about the topic of leaders as coaches having written several papers and columns. My research, and writing led Penguin to commission my book Coaching: The Secret Code to Uncommon Leadership that, released globally in late 2021 to much acclaim, is recommended by several academics as an essential read for aspiring and experienced managers.
A few years ago at my son’s annual townhall in school, the principal outlined the school’s strategic game plan on a powerpoint presentation.
One of the slides that stayed with me projected a visual from the book The End of Average: How We Succeed in a World That Values Sameness.
I went back and read the book, only to realize that it resonated deeply with how we in the corporate world today (not just in schools at the elementary, middle, or senior levels) are quick to pronounce verdicts: below average, average, exceeds expectations.
The book poses some pertinent questions, and rightly so: Who came up with this principle of average? Why are we following it everywhere?
How often have we as managers just given up on people that we perceive are not ‘leadership’ material. Often these same average or poor performers can be great performers in different contexts.
Are you above average? Is your child an A student? Is your employee an introvert or an extrovert? Every day we are measured against the yardstick of averages, judged according to how closely we come to it or how far we deviate from it.
The assumption that metrics comparing us to an average—like GPAs, personality test results, and performance review ratings—reveal something meaningful about our potential is so ingrained in our consciousness that we don’t even question it. That assumption, says Harvard’s Todd Rose, is spectacularly—and scientifically—wrong.
In The End of Average, Rose, a rising star in the new field…
I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.
An authoritative tome on R. This book is the ultimate reference guide, heavy on statistical methods from the simple to the advanced. Of the 29 chapters, only the first five chapters or so have R syntactical and programming skills as their main focus; the remaining content highlights the many and varied statistical techniques R is capable of. I think this is a fantastic book to have on the shelf for people who are likely to need R and its contributed packages for a variety of different statistical analyses, but might not know where to initially start for any given statistical method.
Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: * Features full colour text and extensive graphics throughout. * Introduces a clear structure with numbered section headings to help readers locate information more efficiently. * Looks at the evolution of R over the…
I’ve wanted to be a philosopher since I read Plato’s Phaedo when I was 17, a new immigrant in Canada. Since then, I’ve been fascinated with time, space, and quantum mechanics and involved in the great debates about their mysteries. I saw probability coming into play more and more in curious roles both in the sciences and in practical life. These five books led me on an exciting journey into the history of probability, the meaning of risk, and the use of probability to assess the possibility of harm. I was gripped, entertained, illuminated, and often amazed at what I was discovering.
One day, in conversation with Ian Hacking, he announced a new passion: Archaeology of ideas. The concept we now have of probability was new, he said; it was born in the 17th century and was different from anything before!
I love this book because it is, first of all, a philosopher’s take on history. Hacking confronts the conceptual puzzles that defeated some of the best mathematical minds, raises controversial questions about what it all meant, and gives us a new vision of the history of concepts.
Historical records show that there was no real concept of probability in Europe before the mid-seventeenth century, although the use of dice and other randomizing objects was commonplace. Ian Hacking presents a philosophical critique of early ideas about probability, induction, and statistical inference and the growth of this new family of ideas in the fifteenth, sixteenth, and seventeenth centuries. Hacking invokes a wide intellectual framework involving the growth of science, economics, and the theology of the period. He argues that the transformations that made it possible for probability concepts to emerge have constrained all subsequent development of probability theory and…
Wealth Odyssey is a summary work based on a 12-hour adult education course I taught for 10 years. It’s important to me to educate people through my 29 years in the profession (1994-2023), my focus has always been on helping people first understand that retirement means you’re wealthy enough not to work anymore – working is optional. You don’t need to be rich. Wealth is scalable for any income level and comes from foundation income and investments to supplement that foundation to support your desired lifestyle’s Standard of Individual Living (SOIL) for as long as you live. Your focus should be on your plan and apply a few concepts grounded in well researched evidence.
When people think of financial planning, their first thought is investing. Their second thought is retirement.
Kaplans explain risk succinctly: “Everything is possible, yet only one thing happens.” People understand risk but don’t really understand how to apply it rationally to investing (market risks) or to retirement (longevity risk).
But first, having an understanding of what risk is and isn’t, and where it comes from is important before you can apply it to what fuels your plans – markets and longevity.
This book helped me formulate the basic planning concepts I use in my book since personal finance is all about taking risks – as are any other decisions and actions you take in life.
A compelling journey through history, mathematics, and philosophy, charting humanity’s struggle against randomness
Our lives are played out in the arena of chance. However little we recognize it in our day-to-day existence, we are always riding the odds, seeking out certainty but settling—reluctantly—for likelihood, building our beliefs on the shadowy props of probability. Chances Are is the story of man’s millennia-long search for the tools to manage the recurrent but unpredictable—to help us prevent, or at least mitigate, the seemingly random blows of disaster, disease, and injustice. In these pages, we meet the brilliant individuals who developed the first abstract…
Possibly
the best popular science book I’ve ever read.
Palmer explores the nature of
mathematically chaotic systems and shows how we can deal better with the
uncertainty they embody.
Many real-world systems, from something as complex as
the weather to something as simple as a jointed pendulum, are chaotic, meaning
that they are hard to predict as very small changes in the way they are set up
produce vast differences in outcome.
Palmer covers a whole series of different
topics, in several cases giving the best explanation I’ve ever seen. It’s not
that this is an easy read. I had to go back over a couple of sections to really
take them in – but it was very rewarding.
“Quite possibly the best popular science book I’ve ever read” (Popular Science) shows how the tools that enabled us to overcome the uncertainty of the weather will enable us to find new answers to modern science's most pressing questions
Why does your weather app say “There’s a 10% chance of rain” instead of “It will be sunny tomorrow”? In large part this is due to the insight of Tim Palmer, who made uncertainty essential to the study of weather and climate. Now he wants to apply it to how we study everything else.
