Here are 100 books that Games, Gods and Gambling fans have personally recommended if you like
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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 often think of the ways my life could have gone differently. Career-changing emails that were only narrowly rescued from spam folders, for example. In many parallel timelines, I doubt I’m still doing what I do today—which makes me cherish my good fortune to still be doing it. What I do is study the ways people have come to understand everything can go otherwise and that the future is, therefore, an open question and undecided matter. Of course, for ages, many have instead assumed that events can only go one way. But the following books persuasively insist history isn’t dictated by destiny, but is governed by chance and (sometimes) choice.
Hacking writes in pellucid prose. Reading this book—in an old, dusty library many years ago—is what convinced me, for better or worse, that uncovering the history of ideas was something not only that could be viably done but could be done rigorously.
Hacking’s book tells the story of the emergence of one of the areas of mathematics that arguably shapes our world today more than any other: probability. It governs financial markets as much as military decisions, carving up the edges of our world.
Rewinding to the beginning of the modern age, Hacking tells the story of how an Italian gambler from the 1500s—one Gerolamo Cardano—haphazardly discovered the science of measuring chances and the art of taking them, unwittingly creating the fields of actuary and insurance that shape the foundation of our modern world.
It is riveting stuff: don’t let the mathematical topic put you off. Though this book is…
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…
Tap Dancing on Everest, part coming-of-age memoir, part true-survival adventure story, is about a young medical student, the daughter of a Holocaust survivor raised in N.Y.C., who battles self-doubt to serve as the doctor—and only woman—on a remote Everest climb in Tibet.
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…
In sixth grade, my teacher tried to teach the class how to read line charts – and something fell into place for me. Ever since then, I’ve tried to sort data into forms that we can use to make sense of it. As a researcher at Microsoft, I consulted with teams across the organization – from sales to legal; and from Excel to XBox – to help them understand their data. At Honeycomb, I design tools for software operations teams to diagnose their complex systems. These books each gave me an “ah-hah” moment that made me think differently about the craft of creating visualization. They now sit on my shelf in easy reach – I hope you find them fascinating too.
I learned Tukey’s name about as soon as I learned that data visualization existed as more than a menu in Excel and a personal obsession. Tukey coined the term “exploratory data analysis,” and so tapped into a passion for swimming around in all the interesting rows and columns. Tukey was working before computers were widespread, and so I got a view of how he saw data: working against the constraints of pencil and paper; keeping your hand moving as fast as possible. While the explorations we can do with gigabytes of memory and powerful rendering are very different, the goal of getting information into your head as fast as possible is unchanged.
This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearson.com/statistics-classics-series for a complete list of titles.
The approach in this introductory book is that of informal study of the data. Methods range from plotting picture-drawing techniques to rather elaborate numerical summaries. Several of the methods are the original creations of the author, and all can be carried out either with pencil or aided by hand-held calculator.
0134995457 / 9780134995458 EXPLORATORY DATA ANALYSIS (CLASSIC VERSION), 1/e
I’ve been fascinated by information technology since I was a child–whether in the form of books, libraries, computers, or cell phones! Living through a massive expansion in the volume of data, I believe it is essential to study the long history of information to make sense of our current data-driven times–which is why I became a historian of data, which I teach and write about full time. Here are some of the most informative and insightful books that have helped me make sense of our issues, ranging from information overload and artificial intelligence to privacy and data justice.
Finding yourself overwhelmed, confused, or just plain curious about artificial intelligence?
Then this is the book for you! Wiggins and Jones provide a lucid, comprehensive overview of how we arrived at our current data-saturated times and how artificial intelligence emerged from the political climate of the Cold War as one attempt in a longer history of the ties between political power and information.
I found myself constantly surprised and enlightened by the history of data sketched out by Wiggins and Jones!
From facial recognition-capable of checking us onto flights or identifying undocumented residents-to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the birth of eugenics in Victorian Britain to the development of Google search.
Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing…
In my career as an academic librarian, I was often asked to teach students to think about the credibility of the information they incorporate into their academic, professional, personal, and civic lives. In my teaching and writing, I have struggled to make sense of the complex and nuanced factors that make some information more credible and other information less so. I don’t have all the answers for dealing with problematic information, but I try hard to convince people to think carefully about the information they encounter before accepting any of it as credible or dismissing any of it as non-credible.
I constantly recommend The Data Detective because it serves as an unmatched handbook for making sense of the statistical data to which we are constantly exposed.
What I like about it, besides its lively, readable style, is that the book convincingly and clearly explains 1) why we need statistical data to make informed decisions, 2) the factors that go into producing reliable statistics, 3) the factors that can produce unreliable statistics, and 4) how any statistics, reliable or not, can be misused to deceive us.
The author, Tim Harford, is an economist who writes for the Financial Times and hosts the brilliant podcast Cautionary Tales.
From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics.
Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss…
I've had a long-time interest in two things: mathematics and social issues. This is why I got degrees in social work (Masters) and sociology (PhD) and eventually focused on the quantitative aspects of these two areas. Social Workers Count gave me the chance to marry these two interests by showing the role mathematics can play in illuminating a number of pressing social issues.
Jun Otsuka, a philosopher who also has training in statistics, zooms in on their philosophical foundations.
His book discusses the metaphysical, epistemological, and semantic assumptions on which Classical statistics, Bayesian statistics, predictive/classification AI models, and causal inference are based.
For those interested in these disciplines but who're also sensitive to the philosophical issues they raise, Otsuka's book is simply amazing. Run out and get a copy as soon as possible.
Simply stated, this book bridges the gap between statistics and philosophy. It does this by delineating the conceptual cores of various statistical methodologies (Bayesian/frequentist statistics, model selection, machine learning, causal inference, etc.) and drawing out their philosophical implications. Portraying statistical inference as an epistemic endeavor to justify hypotheses about a probabilistic model of a given empirical problem, the book explains the role of ontological, semantic, and epistemological assumptions that make such inductive inference possible. From this perspective, various statistical methodologies are characterized by their epistemological nature: Bayesian statistics by internalist epistemology, classical statistics by externalist epistemology, model selection by pragmatist…
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.
This provides a superb balance between technical aspects of R coding and the statistical methods that motivate its use. It's rare to find a book on topics like this that are written with Kabacoff's easygoing yet precise style, which makes it ideal for beginners. From my own experience, it is obvious the author has spent many years teaching this type of content, knowing where things deserve extra explanation up front and where other more technical details can be relegated to more advanced texts.
R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.
R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that…
Activating Our 12-Stranded DNA
by
Ruslana Remennikova,
In this vibrant guidebook, sound healer and former corporate scientist Ruslana Remennikova reveals how, through vibration and intention, you can shapeshift DNA from the standard double helix to its 12-stranded, dodecahedral form—unlocking your spiritual potential and opening the way for deep healing of the past, the present, and the future…
I’m a historian who’s spent far too much time thinking about how the color magenta contributed to climate change and why eighteenth-century humanitarians were obsessed with tobacco enemas. My favorite historical topics—like sensation, color, and truth—don’t initially seem historical, but that’s exactly why they need to be explored. I’ve learned that the things that seem like second nature are where our deepest cultural assumptions and unconscious biases hide. In addition to writing nonfiction, I’ve been lucky enough to grow up on a ranch, live in Paris, work as an interior design writer, teach high school and college, and help stray dogs get adopted.
I had never really given much thought to counting until I read this book, but in the very first chapter, Stone made me rethink everything I thought I knew about “one fish, two fish, red fish, blue fish.” She shows that every time we count, we’re making cultural assumptions. For example, what counts as a fish? And what makes the color of the fish more relevant than other features? Counting reveals that while these choices may seem intuitive, basic, and meaningless, they have very real impacts on people’s lives. Especially when we use numbers to measure things like merit, poverty, race, and productivity, those fundamental assumptions matter more than we care to admit.
Early in her extraordinary career, Deborah Stone wrote Policy Paradox, a landmark work on politics. Now, in Counting, she revolutionises how we approach numbers and shows how counting shapes the way we see the world. Most of us think of counting as a skill so basic that we see numbers as objective, indisputable facts. Not so, says Stone. In this playful-yet-probing work, Stone reveals the inescapable link between quantifying and classifying, and explains how counting determines almost every facet of our lives-from how we are evaluated at work to how our political opinions are polled to whether we get into…