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Book Cover for: Dark Data: Why What You Don't Know Matters, David J. Hand

Dark Data: Why What You Don't Know Matters

David J. Hand

A practical guide to making good decisions in a world of missing data

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.

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.

Today, we all make decisions using data. Dark Data shows us all how to reduce the risk of making bad ones.

Book Details

  • Publisher: Princeton University Press
  • Publish Date: Feb 15th, 2022
  • Pages: 344
  • Language: English
  • Edition: undefined - undefined
  • Dimensions: 5.50in - 8.40in - 0.90in - 0.90lb
  • EAN: 9780691234465
  • Categories: Probability & Statistics - GeneralData Science - Data AnalyticsData Science - Data Warehousing

About the Author

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.

More books by David J. Hand

Book Cover for: Statistics: A Very Short Introduction, David J. Hand
Book Cover for: The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day, David J. Hand
Book Cover for: Measurement: A Very Short Introduction, David J. Hand
Book Cover for: Principles of Data Mining, David J. Hand
Book Cover for: Handbook of Small Data Sets, David J. Hand
Book Cover for: Roc Curves for Continuous Data, Wojtek J. Krzanowski
Book Cover for: ROC Curves for Continuous Data, Wojtek J. Krzanowski
Book Cover for: A Handbook of Small Data Sets, David J. Hand
Book Cover for: Analysis of Repeated Measures, Martin J. Crowder
Book Cover for: Artificial Intelligence Frontiers in Statistics: Al and Statistics III, David J. Hand
Book Cover for: Statistics in Finance, David J. Hand
Book Cover for: Construction and Assessment of Classification Rules, David J. Hand
Book Cover for: Artificial Intelligence and Psychiatry, David J. Hand
Book Cover for: The Wellbeing of Nations: Meaning, Motive and Measurement, Paul Allin
Book Cover for: From Gdp to Sustainable Wellbeing: Changing Statistics or Changing Lives?, Paul Allin

Praise for this book

"[A] penetrating study of missing ('dark') data and its impacts on decisions--skewing stats, enabling fraud, embedding inequity and triggering preventable catastrophes. Advocating 'data science judo, ' Hand offers expert training, from recognizing when facts are being cherry-picked to designing randomized trials. A book illuminating shadowed corners in science, medicine and policy."---Barbara Kiser, Nature
"A tour de force. . . . Hand is a good and able guide to take us through the many aspects of dark data that are potentially skewing our understanding of real world observations and potential scientific breakthroughs. He writes in an accessible and understandable way too."---Simon Cocking, Irish Tech News
"Well-written and accessible."---Tim Harford, Undercover Economist
"You need to read [Dark Data], and be convinced by David's reasoning and his examples of cases in which unseen or unreported data play a critical and sometimes even a fatal role. You are likely to walk away with the feeling that the term dark data is indeed a very effective one to arouse both curiosity and suspicion, mixed with happiness that finally a great term was coined by a statistician--and sadness that the statistician is not you."---Xiao-Li Meng, IMS Bulletin
"An exploration of a major problem in data analysis with an attempt of classification, analysing causes, mechanisms, and to some extent also suggest mitigations."---Adhemar Bultheel, European Mathematical Society
"An excellent guide to the many reasons for caution in interpreting data."---Diane Coyle, Enlightened Economist