The Art of Statistics: Learning from Data
Spiegelhalter (David)
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Back Cover Blurb

  1. How can statistics help us understand the world?
  2. Can we come to reliable conclusions when data is imperfect?
  3. How is statistics changing in the age of data science?
  4. Sir David John Spiegelhalter is a British statistician and Chair of the Winton Centre for Risk and Evidence Communication in the Statistical Laboratory at the University of Cambridge. Spiegelhalter is one of the most cited and influential researchers in his field, and was elected as President of the Royal Statistical Society for 2017-18.

How can statistics help us understand the world?1
  1. Does going to University increase the risk of getting a brain tumour?
    • An ambitious study conducted on over 4 million Swedish men and women whose tax and health records were linked over eighteen years enabled researchers to report that men with a higher socioeconomic position had a slightly increased rate of being diagnosed with a brain tumour.
    • But did all that sweating in the library overheat the brain and lead to some strange cell mutations? The authors of the paper doubted it: ‘Completeness of cancer registration and detection bias are potential explanations for the findings.’ In other words, wealthy people with higher education are more likely to be diagnosed and get their tumour registered, an example of ascertainment bias.
  2. How many sexual partners have people in Britain really had?
    • Plotting the responses from a recent UK survey revealed various features, including a (very) long tail, a tendency to use round numbers such as 10 and 20, and more partners reported by men than women. It is incredibly easy to just claim that what these respondents say accurately represents what is really going on in the country. Media surveys about sex, where people volunteer to say what they get up to behind closed doors, do this all the time.
  3. What is the risk of cancer from bacon sandwiches?
    • An IARC report concluded that, normally, 6 in every 100 people who do not eat bacon daily would be expected to get bowel cancer. If 100 similar people ate a bacon sandwich every single day of their lives, the IARC would expect an 18% increase in cases of bowel cancer, i.e. a rise from 6 to 7 cases out of 100. That is one extra case in all those 100 lifetime bacon-eaters, which does not sound as impressive as the relative risk (an 18% increase) and might serve to put this hazard into perspective.
  4. Do busier hospitals have higher survival rates?
    • There is a considerable interest in the so-called ‘volume effect’ in surgery – the claim that busier hospitals get better survival rates, possibly since they achieve greater efficiency and have more experience.
    • When considering English hospitals conducting children’s heart surgery in the 1990s, and plotting the number of cases against their survival, the high correlation showed that bigger hospitals were associated with lower mortality. But we could not conclude that bigger hospitals caused the lower mortality. We cannot conclude that the higher survival rates were in any sense caused by the increased number of cases – in fact it could even be the other way round: better hospitals simply attracted more patients.

    List of Figures – ix
    List of Tables – xiii
    Acknowledgements – xv
    Introduction – 1
  1. Getting Things in Proportion: Categorical Data and Percentages – 19
  2. Summarizing and Communicating Numbers. Lots of Numbers – 39
  3. Why Are We Looking at Data Anyway? Populations and Measurement – 73
  4. What Causes What? – 95
  5. Modelling Relationships Using Regression – 121
  6. Algorithms, Analytics and Prediction – 143
  7. How Sure Can We Be About What Is Going On? Estimates and Intervals – 189
  8. Probability - the Language of Uncertainty and Variability – 205
  9. Putting Probability and Statistics Together – 229
  10. Answering Questions and Claiming Discoveries – 253
  11. Learning from Experience the Bayesian Way – 305
  12. How Things Go Wrong – 341
  13. How We Can Do Statistics Better – 361
  14. In Conclusion – 379
    Glossary – 381
    Notes – 407


In-Page Footnotes ("Spiegelhalter (David) - The Art of Statistics: Learning from Data")

Footnote 1:

Pelican (13 Feb. 2020)

Text Colour Conventions (see disclaimer)
  1. Blue: Text by me; © Theo Todman, 2020
  2. Mauve: Text by correspondent(s) or other author(s); © the author(s)

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