Here are 26 books that The Emergence of Probability fans have personally recommended if you like
The Emergence of Probability.
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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.
Can you love a book that you disagree with? I do! I love this extravagant account of how Bayesian Statistics was enmired in controversy and, after 200 years, saved everything from Western Civilization to Captain Dreyfus.
I don’t think that Bayesian statistics is the foundation of all rational thought, but I am happy to celebrate all its wonderful achievements. Every page of this book is lively and personal, engrossing, entertaining, masterful…all of that.
A New York Times Book Review Editor's Choice: A vivid account of the generations-long dispute over Bayes' rule, one of the greatest breakthroughs in the history of applied mathematics and statistics
"An intellectual romp touching on, among other topics, military ingenuity, the origins of modern epidemiology, and the theological foundation of modern mathematics."-Michael Washburn, Boston Globe
"To have crafted a page-turner out of the history of statistics is an impressive feat. If only lectures at university had been this racy."-David Robson, New Scientist
Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new…
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.
I am laughing out loud, even now that I am rereading this book for the umpteenth time. Fraudsters are so clever, and so is advertising. And then there is sloppy journalism with its “wow” statistics.
I like his book enormously, not least because of its witty illustrations. It is subversive, comic, and provocative, and it makes me wise to seductive, misleading practices–and it does so with a light touch.
From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff's lively and engaging primer clarifies the basic principles of statistics and explains how they're used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
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.
I found a copy of this book in the sixties. That copy, much loved, was lost in moves and mayhem. Now, I only have a Dover reprint (water-logged during yet another move), but I have never been without and would search high and low if I were.
This is also a history of probability but with a very different focus. Ms. David was a statistician able to explain the calculations intuitively (good to assign to my students). But she was also thoroughly interested in the personalities involved. What was Galileo like? What happened to Pascal at Port-Royal?
I felt personally drawn into the historical narrative that often reads like a novel.
The development of gambling techniques led to the beginning of modern statistics, and this absorbing history illustrates the science's rise with vignettes from the lives of Galileo, Fermat, Pascal, and others. Fascinating allusions to the classics, archaeology, biography, poetry, and fiction endow this volume with universal appeal. 1962 edition.
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.
I love this book because it builds practical advice on a philosophical critique.
Can philosophy generate truly practical advice for planning and public policy? Randomized Controlled Trials are the gold standard for evidence in industrial planning and public policy. But if the results are taken naively, they mislead.
I’m a long-time fan of author Nancy Cartwright, a McArthur Genius Award winner. I love her provocative approach when abstract thought has to confront real practice.
Over the last twenty or so years, it has become standard to require policy makers to base their recommendations on evidence. That is now uncontroversial to the point of triviality--of course, policy should be based on the facts. But are the methods that policy makers rely on to gather and analyze evidence the right ones? In Evidence-Based Policy, Nancy Cartwright, an eminent scholar, and Jeremy Hardie, who has had a long and successful career in both business and the economy, explain that the dominant methods which are in use now--broadly speaking, methods that imitate standard practices in medicine like randomized…
My father was an artist who painted passionately, almost always outdoors. When I told him I wanted to become an art historian, he was sad partly because he hated art historians, but mainly because he imagined me chained (as a writer) to a desk, rather than marching the countryside looking for things to paint or draw. Like most writers, I sometimes get seriously bogged down, and his sadness comes back to haunt me. But then I pick up a book that, in just a few pages, puts my writing back on track, gladdening my father’s ghost.
Are you stuck on a single sentence that keeps expanding but goes nowhere? Then tame it by cutting it down and finishing it off now. Ian Hacking is the master of the subject-verb-predicate sentence in historical writing. And this book, in addition to being a model of stylistic clarity, changes how we think about modernity, mathematics, danger, and risk. You’ll never be afraid of being clear again.
In this important study Ian Hacking continues the enquiry into the origins and development of certain characteristic modes of contemporary thought undertaken in such previous works as the best-selling The Emergence of Probability. Professor Hacking shows how by the late-nineteenth century it became possible to think of statistical patterns as explanatory in themselves, and to regard the world as not necessarily deterministic in character. In the same period the idea of human nature was displaced by a model of normal people with laws of dispersion. These two parallel transformations fed into each other, so that chance made the world seem…
My interest in this topic began after my father died when I was a young teenager and I was left looking for answers, explanations, and meanings. My dad was an architect and had written a book on Jeremy Bentham’s panoptican and prison architecture published before the French philosopher Michel Foucault’s famous Discipline and Punish. A small collection of Foucault’s books stood prominently on my father’s bookshelves and I really wanted to understand them. At university I studied all of Foucault’s works and many authors inspired by him. These are the best books that explain how we have developed philosophical and psychological theories to understand ourselves in the contemporary world.
Forrester’s excellent, yet sadly unfinished, Thinking in Cases, advanced a radical new way to consider the history of the human sciences and their modelling of the self or the individual. Whereas Hacking and Foucault focused on population-based statistical styles of reasoning as the means by which the modern state operated, Forrester argues that these ‘styles of reasoning’ were always supported by what he has termed ‘case-based reasoning.’ In doing so, Forrester considers how biopolitical power has been advanced via both legal and medical cases. He describes his approach as being informed by ‘three rhizomic structures,’ namely ‘the psychoanalytic case history; the historical sociology of the sciences; and the individual in the human sciences.’ This rhizomic model is unique to Forrester’s approach, and allows him to move freely between law, anthropology, medicine, politics, psychoanalysis, and the social sciences, in his reflections on the case. He asks us to reflect on…
What exactly is involved in using particular case histories to think systematically about social, psychological and historical processes? Can one move from a textured particularity, like that in Freud's famous cases, to a level of reliable generality? In this book, Forrester teases out the meanings of the psychoanalytic case, how to characterize it and account for it as a particular kind of writing. In so doing, he moves from psychoanalysis to the law and medicine, to philosophy and the constituents of science. Freud and Foucault jostle here with Thomas Kuhn, Ian Hacking and Robert Stoller, and Einstein and Freud's connection…
My interest in this topic began after my father died when I was a young teenager and I was left looking for answers, explanations, and meanings. My dad was an architect and had written a book on Jeremy Bentham’s panoptican and prison architecture published before the French philosopher Michel Foucault’s famous Discipline and Punish. A small collection of Foucault’s books stood prominently on my father’s bookshelves and I really wanted to understand them. At university I studied all of Foucault’s works and many authors inspired by him. These are the best books that explain how we have developed philosophical and psychological theories to understand ourselves in the contemporary world.
The brilliant Rewriting the Soul was published in the mid-1990s when the diagnosis of multiple personality disorder was booming, particularly in the USA. The text reflects these times in its focus on the sciences of memory from the late 19th century. Hacking links discussions on memory, trauma, and consciousness in the study of multiple personalities in the 1980s and relates these to earlier discussions on ‘double consciousness’ in the 19th century. He argues that contemporary liberal societies have become obsessed with individual memory and how to analyse and assess it. Hacking skilfully weaves together historical and philosophical perspectives to explore case studies in depth. He questions how and why facts about our memories have become so important in contemporary culture, and how psychiatry has always struggled with interpreting the meaning of memory for its subjects. We are left with a deeper understanding of how a diagnosis ascribed to so many…
Twenty-five years ago one could list by name the tiny number of multiple personalities recorded in the history of Western medicine, but today hundreds of people receive treatment for dissociative disorders in every sizable town in North America. Clinicians, backed by a grassroots movement of patients and therapists, find child sexual abuse to be the primary cause of the illness, while critics accuse the "MPD" community of fostering false memories of childhood trauma. Here the distinguished philosopher Ian Hacking uses the MPD epidemic and its links with the contemporary concept of child abuse to scrutinize today's moral and political climate,…
I am a financial data scientist. I think it is important that data scientists are highly specialized if they want to be effective in their careers. I run a business called Conlan Scientific out of Charlotte, NC where me and my team of financial data scientists tackle complicated machine learning problems for our clients. Quant trading is a gladiator’s arena of financial data science. Anyone can try it, but few succeed at it. I am sharing my top five list of math books that are essential to success in this field. I hope you enjoy.
Everyone knows what probability is, and we all understand how a coin flip works, but not everyone can explain the optimal betting strategies for a roulette table. We don’t study probability to understand the likelihood of events. We study probability to understand the expected outcomes of business processes that depend on those events.
In other words, this book won’t just teach you about probabilities, it will teach you about business strategies associated with those probabilities. It will help you answer a question like: How do I maximize the profit on this life insurance policy, given this set of survival probabilities? It isn’t just a likelihood question, it is a business question. I highly recommend that anyone studying probability does so through an actuarial lens.
This book covers the basic probability of distributions with an emphasis on applications from the areas of investments, insurance, and engineering. Written by a Fellow of the Casualty Actuarial Society and the Society of Actuaries with many years of experience as a university professor and industry practitioner, the book is suitable as a text for senior undergraduate and beginning graduate students in mathematics, statistics, actuarial science, finance, or engineering as well as a reference for practitioners in these fields. The book is particularly well suited for students preparing for professional exams, and for several years it has been recommended as…
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…
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
My knees tremble and my heart quakes when I think of how much work must have gone into these two companion volumes. Collectively, they are more than four times the length of my book, covering the whole of machine learning.
It is an essential encyclopedic resource that should be on the desk of anyone serious about machine learning.
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.
This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.
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