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Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best.The 9 Pitfalls of Data Science shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession.Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.
This book investigates the core question of how common analytical errors and cognitive biases in data science lead to significant real-world failures. Gary Smith, a professor of economics, and journalist Jay Cordes utilize a series of historical and contemporary case studies to demonstrate how the misuse of statistical models and the reliance on machine-generated patterns can result in catastrophic decision-making. The authors argue that technical proficiency must be paired with rigorous critical thinking to avoid the pitfalls of Big Data.
What You Will Find
Experts and readers frequently note that this text serves as a necessary cautionary volume for practitioners and laypeople alike. The prose is described as accessible and engaging, making complex statistical concepts understandable for those without a formal background in data science.
Page Count:
272
Publication Date:
2019-09-01
Publisher:
Oxford University Press
ISBN-10:
0198844395
ISBN-13:
9780198844396
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