Podcast appearances and mentions of David J Hand

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida.

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/economics

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science-technology-and-society

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/finance

The science behind miracles. Have you ever encountered something so striking that it made you say, “That’s a miracle!” Or perhaps you’ve experienced a phenomenon that makes you feel as though it’s too extraordinary to ever happen by chance. But the research of professor and statistician David J. Hand indicates that what we consider miraculous is actually both ordinary and easily predicted according to something called the improbability principle. This book unpacks the science and statistics behind seemingly miraculous phenomena. Do you want more free book summaries like this? Download our app for free at https://www.QuickRead.com/App and get access to hundreds of free book and audiobook summaries. DISCLAIMER: This book summary is meant as a preview and not a replacement for the original book. If you like this summary please consider purchasing the original book to get the full experience as the original author intended to. If you are the original author of any book on QuickRead and would like us to remove it, please contact us at hello@quickread.com

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand’s new book Dark Data: Why What You Don’t Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those...

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida.

There is no shortage of books on the growing impact of data collection and analysis on our societies, our cultures, and our everyday lives. David Hand's new book Dark Data: Why What You Don't Know Matters (Princeton University Press, 2020) is unique in this genre for its focus on those data that aren't collected or don't get analyzed. More than an introduction to missingness and how to account for it, this book proposes that the whole of data analysis can benefit from a "dark data" perspective—that is, careful consideration of not only what is seen but what is unseen. David assembles wide-ranging examples, from the histories of science and finance to his own research and consultancy, to show how this perspective can shed new light on concepts as classical as random sampling and survey design and as cutting-edge as machine learning and the measurement of honesty. I expect the book to inspire the same enjoyment and reflection in general readers as it is sure to in statisticians and other data analysts. Suggested companion work: Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men. Cory Brunson (he/him) is a Research Assistant Professor at the Laboratory for Systems Medicine at the University of Florida. Learn more about your ad choices. Visit megaphone.fm/adchoices

The science behind miracles. Have you ever encountered something so striking that it made you say, “That’s a miracle!” Or perhaps you’ve experienced a phenomenon that makes you feel as though it’s too extraordinary to ever happen by chance. But the research of professor and statistician David J. Hand indicates that what we consider miraculous is actually both ordinary and easily predicted according to something called the improbability principle. This book unpacks the science and statistics behind seemingly miraculous phenomena. *** Do you want more free audiobook summaries like this? Download our app for free at QuickRead.com/App and get access to hundreds of free book and audiobook summaries.

My guest today is David J. Hand, an emeritus professor of mathematics and senior research investigator at Imperial College London, a former president of the Royal Statistical Society, and a fellow of the British Academy. His many previous books include The Improbability Principle, Measurement: A Very Short Introduction, Statistics: A Very Short Introduction, and Principles of Data Mining. The topic is his book Dark Data: Why What You Don't Know Matters. In this episode of Trend Following Radio we discuss: David Hand Improbability principle Statistics Underestimating variability Improbability principles Fabricated data Social Sciences Jump in! --- I'm MICHAEL COVEL, the host of TREND FOLLOWING RADIO, and I'm proud to have delivered 10+ million podcast listens since 2012. Investments, economics, psychology, politics, decision-making, human behavior, entrepreneurship and trend following are all passionately explored and debated on my show. To start? I'd like to give you a great piece of advice you can use in your life and trading journey… cut your losses! You will find much more about that philosophy here: https://www.trendfollowing.com/trend/ You can watch a free video here: https://www.trendfollowing.com/video/ Can't get enough of this episode? You can choose from my thousand plus episodes here: https://www.trendfollowing.com/podcast My social media platforms: Twitter: @covel Facebook: @trendfollowing LinkedIn: @covel Instagram: @mikecovel Hope you enjoy my never-ending podcast conversation!

Today on Trend Following Radio Michael Covel talks with David Hand. In the era of big data, it is easy to imagine that we have all the information we need to make good decisions. But in fact the data we have are never complete, and may be only the tip of the iceberg. Just as much of the universe is composed of dark matter, invisible to us but nonetheless present, the universe of information is full of dark data that we overlook at our peril. In Dark Data, data expert David Hand takes us on a fascinating and enlightening journey into the world of the data we don’t see. David Hand’s Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them. In doing so, he teaches us not only to be alert to the problems presented by the things we don’t know, but also shows how dark data can be used to our advantage, leading to greater understanding and better decisions. Biography: David J. Hand is emeritus professor of mathematics and senior research investigator at Imperial College London, a former president of the Royal Statistical Society, and a fellow of the British Academy. His many previous books include The Improbability Principle, Measurement: A Very Short Introduction, Statistics: A Very Short Introduction, and Principles of Data Mining.

Are miracles nothing more than statistical probabilities? Are unobserved rare events happening around us all the time? Can you give yourself better odds at wining the lottery? In episode 12 we speak with distinguished statistician, Professor David J. Hand, about his book: The Improbability Principle – Why Coincidences, Miracles and Rare Events Happen Every Day. The odds are very favourable that you will enjoy this interview.

David J. Hand , emeritus professor of mathematics at Imperial College London, talks about his new book The Improbability Principle: Why Coincidences, Miracles and Rare Events Happen Every Day

Just like in The Wizard of Oz, sometimes it seems that events, coincides and serendipitous good fortune happen as part of a grand plan.  Later we think that it’s the the result of a great and powerful force pulling the ropes and levers.  Only much later do we discover that events happen on their own, and it’s only in a dream, driven by our penchant to find order and connection, that the events are tied together.For many of us this happens all the time.  Thinking about an old friend who suddenly shows up or gets in touch, or a near miss of an accident that feels like an invisible hand saved us, or  finding something from the distant past at precisely the moment we need it.  All of these are examples of the The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day. And now, thanks to David J. Hand, we have a new and much clearer understanding of why it works.My conversation with David Hand:

Why you shouldn't be surprised when the same six winning lottery numbers come up in successive drawings, by David J. Hand

Why you shouldn't be surprised when the same six winning lottery numbers come up in successive drawings, by David J. Hand