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Art of Statistics: How to Learn from Data [Minkštas viršelis]

4.16/5 (5422 ratings by Goodreads)
  • Formatas: Paperback / softback, 448 pages, aukštis x plotis x storis: 208x137x33 mm, weight: 386 g, Illustrations, unspecified
  • Išleidimo metai: 17-Aug-2021
  • Leidėjas: Basic Books
  • ISBN-10: 1541675703
  • ISBN-13: 9781541675704
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 448 pages, aukštis x plotis x storis: 208x137x33 mm, weight: 386 g, Illustrations, unspecified
  • Išleidimo metai: 17-Aug-2021
  • Leidėjas: Basic Books
  • ISBN-10: 1541675703
  • ISBN-13: 9781541675704
Kitos knygos pagal šią temą:
In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life&;s biggest problems.  
 
The age of big data has made statistical literacy more important than ever. In The Art of Statistics, David Spiegelhalter shows how to apply statistical reasoning to real-world problems. Whether we're analyzing preventative medical screening or the terrible crime sprees of serial killers, Spiegelhalter teaches us how to clarify questions, assumptions, and expectations and, most importantly, how to interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to the power of data.
 
"A call to arms for greater societal data literacy . . . a reminder that there are passionate, self-aware statisticians who can argue eloquently that their discipline is needed now more than ever." -- Financial Times
List Of Figures
xi
List Of Tables
xiii
Acknowledgements xv
Introduction 1(18)
Chapter 1 Getting Things in Proportion: Categorical Data and Percentages
19(20)
Chapter 2 Summarizing and Communicating Numbers. Lots of Numbers
39(34)
Chapter 3 Why Are We Looking at Data Anyway? Populations and Measurement
73(22)
Chapter 4 What Causes What?
95(26)
Chapter 5 Modelling Relationships Using Regression
121(22)
Chapter 6 Algorithms, Analytics and Prediction
143(46)
Chapter 7 How Sure Can We Be About What Is Going On? Estimates and Intervals
189(16)
Chapter 8 Probability - the Language of Uncertainty and Variability
205(24)
Chapter 9 Putting Probability and Statistics Together
229(24)
Chapter 10 Answering Questions and Claiming Discoveries
253(52)
Chapter 11 Learning from Experience the Bayesian Way
305(36)
Chapter 12 How Things Go Wrong
341(20)
Chapter 13 How We Can Do Statistics Better
361(18)
Chapter 14 In Conclusion
379(2)
Glossary 381(26)
Notes 407(12)
Index 419