David Spiegelhalter > Quotes

“Even in an era of open data, data science and data journalism, we still need basic statistical principles in order not to be misled by apparent patterns in the numbers.”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“Signals always come with noise: It is trying to separate out the two that makes the subject interesting.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“More data means that we need to be even more aware of what the evidence is actually worth.”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“Far from freeing us from the need for statistical skills, bigger data and the rise in the number and complexity of scientific studies makes it even more difficult to draw appropriate conclusions.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning. — Nate Silver, The Signal and the Noise1”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“When the CERN teams reported a 'five-sigma' result for the Higgs boson, corresponding to a P-value of around 1 in 3.5 million, the BBC reported the conclusion correctly, saying this meant 'about a one-on-3.5 million chance that the signal they see would appear if there were no Higgs particle.' But nearly every other outlet got the meaning of this P-value wrong. For example, Forbes Magazine reported, 'The chances are less than 1 in a million that it is not the Higgs boson,' a clear example of the prosecutor's fallacy. The Independent was typical in claiming that 'there is less than a one in a million chance that their results are a statistical fluke.' This may not be blatantly mistaken as Forbes, but it is still assigning the small probability to 'their results are a statistical fluke', which is logically the same as saying this is the probability of the null hypothesis being tested.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“We need to distinguish what is actually dangerous from what sounds frightening.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“Even after my decades as a statistician, when asked a basic school question using probability, I have to go away, sit in silence with a pen and paper, try it a few different ways, and finally announce what I hope is the correct answer.”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“there is no substitute for simply looking at data properly,”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“Probability theory naturally comes into play in what we shall call situation 1: When the data-point can be considered to be generated by some randomizing device, for example when throwing dice, flipping coins, or randomly allocating an individual to a medical treatment using a pseudo-random-number generator, and then recording the outcomes of their treatment. But in practice we may be faced with situation 2: When a pre-existing data-point is chosen by a randomizing device, say when selecting people to take part in a survey. And much of the time our data arises from situation 3: When there is no randomness at all, but we act as if the data-point were in fact generated by some random process, for example in interpreting the birth weight of our friend’s baby.”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“All models are wrong, but some are useful.’ CHAPTER 6 Algorithms, Analytics and Prediction”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“Most drugs on the market have only moderate effects, and only help a minority of people”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“These examples show that statistics are always to some extent constructed on the basis of judgements, and it would be an obvious delusion to think the full complexity of personal experience can be unambiguously coded and put into a spreadsheet or other software.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“if we do ten trials of useless drugs the chance of getting at least one significant at P < 0.05 gets as high as 40%.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“Alberto Cairo has identified four common features of a good data visualization: It contains reliable information. The design has been chosen so that relevant patterns become noticeable. It is presented in an attractive manner, but appearance should not get in the way of honesty, clarity and depth. When appropriate, it is organized in a way that enables some exploration.”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“I returned and saw under the sun, that the race is not to the swift, nor the battle to the strong, nor bread to the wise, nor riches to men of understanding, nor favour to men of skill; but time and chance happen to them all.

[Quoting Ecclesiastes 9:11 in the epigraph to the Introduction.]”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“Once we accept a personal, subjective view of probability and uncertainty, we are led naturally to Bayesian analysis, in which we use the theory of probability to revise our beliefs in the light of new evidence. These ideas were crucial to Alan Turing’s codebreaking in the Second World War and now help us to interpret imperfect data, such as automated recognition of faces in crowds. We might even have Bayesian brains.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“To statisticians everywhere, with their endearing traits of pedantry, generosity, integrity, and desire to use data in the best way possible”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“This book is primarily concerned with an analytic approach to risk and uncertainty, using numbers, statistical models, and so on, but it’s the feelings about risk that tend to dominate our personal attitudes to the perils we may face.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“The first rule of communication is to shut up and listen,”
― David Spiegelhalter, The Art of Statistics: Learning from Data

“When around 1,000 adults in Germany7 were asked, ‘Would you want to know today when you will die?’, 88% said no (8% were uncertain, and only 4% said yes).”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“This may require facing up to deep uncertainty – limitations of our whole conceptualization of the world, reflecting the boundaries of our ideas as to what could happen. This requires admitting both the gaps in our understanding and the limits to our imagination, and rather than doing yet more complex analysis and trying to produce an optimal course of action, it may be better to seek flexible strategies that should be resilient to most eventualities.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“This constant state of uncertainty is an essential part of the human condition.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“[Adolphe Quetelet] developed the idea of 'social physics', since the regularity of societal statistics seemed to reflect an almost mechanistic underlying process. Just as the random molecules of a gas come together to make predictable physical properties, so the unpredictable workings of millions of individual lives come together to produce, for example, national suicide rates that barely change from year to year.”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“hazard is more ‘dread’ if it is uncontrollable, involuntary, fatal, inequitable and increases risk to future generations – think nuclear accidents. A potential threat is more ‘unknown’ if it is unobservable, novel, and ill-understood – think attitudes to electromagnetic radiation from mobile-phone masts. Familiar activities like cycling, while potentially risky, are neither unknown nor dread.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“It’s vital to remember that the daily counts on the news of the ‘28-day’ death figures do not represent deaths that happened in the last 24 hours, but those newly reported. Figure 11–1 shows a clear weekly cycle: the daily figures tend to be higher on Tuesdays and Wednesdays because of reporting delays over the weekend. This has led to some dramatic differences in England: there were 560 deaths reported on Monday, 18 January 2021, jumping to 1,507 the next day. Since all these numbers are released at around 4 p.m. each day, they become ‘news’ and so are given prominence by journalists, regardless of their relevance.”
― David Spiegelhalter, Covid By Numbers: Making Sense of the Pandemic with Data

“We now know that bin Laden was in the compound, and was killed, presumably vindicating those who had given a high probability to his presence there. Some have argued that the wide diversity of views among the intelligence advisers should have been condensed into a single probability assessment before being presented to Obama13 but, personally, I feel a decision-maker should know when his advisers disagree – Obama needed to synthesize what he was hearing and take ultimate responsibility.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“However, the basic lesson still holds – our concern tends to be not so much related to the uncertainty about whether something will happen, as uncertainty about what it will be like if it does.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck

“Does going to university increase the risk of getting a brain tumour?”
― David Spiegelhalter, The Art of Statistics: How to Learn from Data

“this book is about trying to think slowly about our ‘not-knowing’.”
― David Spiegelhalter, The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck