Here are 54 books that Bayesian Statistics for Beginners fans have personally recommended if you like
Bayesian Statistics for Beginners.
Shepherd is a community of 12,000+ authors and super readers sharing their favorite books with the world.
I am an academic researcher and an avid non-fiction reader. There are many popular books on science or music, but it’s much harder to find texts that manage to occupy the space between popular and professional writing. I’ve always been looking for this kind of book, whether on physics, music, AI, or math – even when I knew that as a non-pro, I wouldn’t be able to understand everything. In my new book I’ve been trying to accomplish something similar: A book that can intrigue readers who are not professional economic theorists, that they will find interesting even if they can’t follow everything.
In the ongoing debates over artificial general intelligence (AGI), Judea Pearl is taking a firm stand: He argues that an intelligent robot should be able to reason about causality and that the currently fashionable approaches to AI miss this aspect.
A celebrated AI researcher and a Turing Prize laureate, Pearl has developed an amazingly original approach to this problem. This book is a high-end popular exposition of his approach.
But it’s so much more than that. It’s a history of statistics and its conflicted attitude to causality. It’s a story of heroes (or villains?) in this history. And it’s a scientific autobiography that describes Pearl’s journey. Pearl likes picking fights with the AI community, statisticians, or economists. He’s boastful, provocative, extremely intelligent, and knows how to tell a story.
'Wonderful ... illuminating and fun to read' - Daniel Kahneman, winner of the Nobel Prize and author of Thinking, Fast and Slow
'"Pearl's accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence and have redefined the term "thinking machine"' - Vint Cerf, Chief Internet Evangelist, Google, Inc.
The influential book in how causality revolutionized science and the world, by the pioneer of artificial intelligence
'Correlation does not imply causation.' This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking…
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.
As I write these lines, artificial intelligence (AI) is getting a lot of attention.
This is largely due to ChatGpt recently bursting onto the scene. But even before ChatGpt began making its mark, AI was often in the news. Some have expressed worry that it will take our jobs, others that it will reinforce systemic oppression by making racially or otherwise discriminatory decisions, and some have even voiced concerns that one day a superintelligent AI might pose an existential threat to humanity.
In the midst of all this, what might get lost is what AI is, what it's capable of doing, and what its limitations are. Wenger's book is intended to address all of these questions. It manages to do so in a way which goes into some of the mathematics of AI systems and yet remain accessible to a lay audience.
Artificial intelligence is everywhere―it’s in our houses and phones and cars. AI makes decisions about what we should buy, watch, and read, and it won’t be long before AI’s in our hospitals, combing through our records. Maybe soon it will even be deciding who’s innocent, and who goes to jail . . . But most of us don’t understand how AI works. We hardly know what it is. In "Is the Algorithm Plotting Against Us?", AI expert Kenneth Wenger deftly explains the complexity at AI’s heart, demonstrating its potential and exposing its shortfalls. Wenger empowers readers to answer the question―What…
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'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.
Many people associate mathematics with calculating things or plugging numbers into formulas to get answers to a multitude of problems.
But this isn't how mathematicians view their discipline. They see mathematics as more about starting with definitions of key mathematical concepts, stating axioms about these concepts, and proving things about them. For those interested in going from calculating and plug and chug mathematics to "real" mathematics, Richard Hammack's book is a terrific place to start.
The book covers a number of topics that cut across all of pure and applied mathematics, topics such as sets, relations, and functions. But the heart of the book is focused on how mathematicians go about proving things. If one wants a glimpse of how mathematicians really work, go out and get this book immediately.
This book is an introduction to the language and standard proof methods of mathematics. It is a bridge from the computational courses (such as calculus or differential equations) that students typically encounter in their first year of college to a more abstract outlook. It lays a foundation for more theoretical courses such as topology, analysis and abstract algebra. Although it may be more meaningful to the student who has had some calculus, there is really no prerequisite other than a measure of mathematical maturity.
Topics include sets, logic, counting, methods of conditional and non-conditional proof, disproof, induction, relations, functions, calculus…
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 love knowing about things. Science is both a knowledge base and a way to discover new knowledge. I’ve been looking through microscopes and telescopes (that my dad built) from my earliest toddling. Though I have never been to university I have picked the brains of my scientific siblings (one of whom is a biology professor) and I read widely. Gathering crumbs from many sources gives a wider knowledge base than one university child afford. Scientists begin with speculation. I love inventing systems and worlds where we break one or a few of our known laws of nature or physics. Marrying science with fantasy births marvelous offspring!
The power of unrequited love that seeks no alternative. A knight loves his queen. He gives his life to protect her and is banished from her presence, yet he cannot resist the magic that arranges the world to draw them together.
Evil tries to convince us that it gives the greatest benefit. Sometimes that is temporarily true. I love stories where characters resist and suffer so that they receive the higher benefit of good. I am a musician and the magic of our knight rings true in my soul.
Highly philosophical, spiritual, fantastical, and deeply scientific, this book satisfies on every level.
“Thermodynamics, signal theory, Bayesian inference, inversion, quantum tunneling, and materials science are all elements of the internally consistent system of dynamics.” Lee Hunt
"This spectacular standalone fantasy bursts with epic battles and avid romance." - Booklife Reviews Editor's Pick
“A beautifully crafted setting with complex character dynamics and layers of political intrigue… A showstopper.Hunt’s ambitious standalone latest has everything—a well-imagined fantasy world, great characters, incredible tension, and fierce love. The real genius here is the mixture of extraordinarily deep worldbuilding with relevant and complex themes, which include identity, intolerance, love, passion, friendship, integrity, honor and more.” - Prairies Book Review
“An intriguing storyline, scenarios grounded in the real world, and a breathless pace make Hunt’s latest standalone fantasy a must-read.” - BookView ReviewsRecommended…
As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!
This book, by Nate Silver of 538 fame, explains in a straightforward manner why so many predictions by “experts,” from weather forecasts to sports outcomes to election polling to economics, ultimately prove wrong.
It relates to understanding the “signal,” the underlying science that is often revealed through trends and patterns in data, relative to the “noise,” the random or unpredictable variations always present in data. Silver also explains the concept of conditional probability, probability when provided with some relevant information, in an unusually clear manner.
The book reads more like a casual conversation with the author, rather than a statistics textbook.
UPDATED FOR 2020 WITH A NEW PREFACE BY NATE SILVER
"One of the more momentous books of the decade." —The New York Times Book Review
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight.
Drawing on his own groundbreaking work, Silver examines the world of prediction,…
John Staddon is James B. Duke Professor of Psychology, and Professor of Biology emeritus. He got his PhD at Harvard and has an honorary doctorate from the Université Charles de Gaulle, Lille 3, France. His research is on the evolution and mechanisms of learning in humans and animals, the history and philosophy of psychology and biology, and the social-policy implications of science. He's the author of over 200 research papers and five books including Adaptive Behavior and Learning,The New Behaviorism: Foundations of behavioral science, 3rd edition, Unlucky Strike: Private health and the science, law and politics of smoking, 2nd edition and Science in an age of unreason.
Any list of books about science must have something about Darwin. The book to read is The Origin. But that’s obvious. I don’t need to go into it. So here is a Darwin book that is less obvious.
Most scientists will never have heard of it; it’s literary history, not science. I learned of it by accident, in a talk given by an economic historian. This is a fascinating book by a literary historian from which I learned much about Darwin. Gillian Beer recognizes that Darwin was a great writer. She traces similarities between his rhetorical style and the strategies of some other iconic Victorian writers, such as George Eliot (Middlemarch) and Samuel Butler (The way of all flesh).
She also discusses scientific writers of the era such as George Lewis and Herbert Spencer. There are many revealing long quotations. I learned much from the…
Gillian Beer's classic Darwin's Plots, one of the most influential works of literary criticism and cultural history of the last quarter century, is here reissued in an updated edition to coincide with the anniversary of Darwin's birth and of the publication of The Origin of Species. Its focus on how writers, including George Eliot, Charles Kingsley and Thomas Hardy, responded to Darwin's discoveries and to his innovations in scientific language continues to open up new approaches to Darwin's thought and to its effects in the culture of his contemporaries. This third edition includes an important new essay that investigates Darwin's…
During my undergraduate studies in psychology, we were never exposed to genetics. In 1970, I began graduate training in psychology at the University of Texas at Austin, which was one of the few universities that had a course about genetics in psychology. The course floored me, and I knew right away that I wanted to study genetic influences in psychology. At that time, psychology was generally hostile to the notion of genetic influence. Now, 50 years later, most psychologists recognize the importance of genetics. The DNA revolution is changing everything by making it possible to predict psychological traits using DNA alone.
“Why most published research findings are false” was a 2005 paper that kicked off a crisis in science about failures to replicate, creating gaping cracks in the bedrock of science. Science Fictions explains this replication crisis and prescribes remedies. The book is written in an entertaining style, which led to its inclusion in the shortlist of the Royal Society Science Book Prize for 2021. Psychology is the poster child for the replication crisis. One of the things I like about genetics is that its findings consistently replicate, beginning with the fundamental finding that about half of the differences between people on psychological traits can be explained by inherited DNA differences.
Shortlisted for the Royal Society Science Book Prize 2021
Medicine, education, psychology, economics - wherever it really matters, we look to science for guidance. But what if science itself can't always be relied on?
In this vital investigation, Stuart Ritchie reveals the disturbing flaws in today's science that undermine our understanding of the world and threaten human lives. With bias, careless mistakes and even outright forgery influencing everything from austerity economics to the anti-vaccination movement, he proposes vital remedies to save and protect science - this most valuable of human endeavours - from itself.…
I’m a children’s book author, illustrator, translator, and book reviewer. I’m the author of Tofu Takes Time, illustrated by Julie Jarema, and Long Goes To Dragon School, illustrated by Mae Besom. I was born and raised in Hefei, China, and moved to the US in my 20s. Being fascinated by the differences and similarities between cultures, I love to share stories that empower children to understand the world and our connections. Children’s picture books have the potential to pass on the joy from generation to generation. As an art lover, I also find it very entertaining and soothing to simply enjoy the artwork of picture books.
Yara is a girl with a passion for science who is determined to make new discoveries. The book has educational back matter explaining the scientific method of making new discoveries and lays out each step in the process clearly that young readers can follow. It will inspire children to start experimenting on their own. Like every good scientist, Yara starts with a question, makes observations, and comes up with a hypothesis... but each time she starts an experiment, her dog, Renzo, ruins it! Yara sets a great example for young readers to pursue scientific studies. In this humorous story, there is clear evidence that scientific method works as well for dogs as for people.
A humorous, endearing story about a passionate, young scientist who is determined to achieve her goal--no matter what!
Yara is out to prove that she's the greatest scientist in town!
Her annoying neighbor Eddie always wins the Science Fair, but this year is going to be HER year. Like every good scientist, Yara starts with a question, makes observations, and comes up with a hypothesis . . . but each time she starts an experiment, her dog, Renzo, ruins it!
Could Renzo be up to something more than making trouble?
From Betsy Ellor and Luisa Vera comes a humorous, endearing…
