Half the participants were told to nod their head up and down while others were told to shake it side to side. The messages they heard were radio edi… - Daniel Kahneman

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Half the participants were told to nod their head up and down while others were told to shake it side to side. The messages they heard were radio editorials. Those who nodded (a yes gesture) tended to accept the message they heard, but those who shook their head tended to reject it. Again, there was no awareness, just a habitual connection between an attitude of rejection or acceptance and its common physical expression. You can see why the common admonition to “act calm and kind regardless of how you feel” is very good advice: you are likely to be rewarded by actually feeling calm and kind.

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About Daniel Kahneman

Daniel Kahneman (March 5, 1934 – March 27, 2024) was an Israeli-American psychologist. He shared the 2002 Nobel Memorial Prize in Economic Sciences with Vernon L. Smith. Kahneman is notable for his work on the psychology of judgment and decision-making, behavioral economics and hedonic psychology. Latterly, he was professor emeritus of psychology and public affairs at Princeton University's Woodrow Wilson School.

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Also Known As

Native Name: דניאל כהנמן
Alternative Names: D Kahneman D. Kahneman Kahneman Kahneman D Kahneman D.
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Additional quotes by Daniel Kahneman

A simple rule can help: before an issue is discussed, all members of the committee should be asked to write a very brief summary of their position. This procedure makes good use of the value of the diversity of knowledge and opinion in the group. The standard practice of open discussion gives too much weight to the opinions of those who speak early and assertively, causing others to line up behind them.

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Dawes observed that the complex statistical algorithm adds little or no value. One can do just as well by selecting a set of scores that have some validity for predicting the outcome and adjusting the values to make them comparable (by using standard scores or ranks). A formula that combines these predictors with equal weights is likely to be just as accurate in predicting new cases as the multiple-regression formula that was optimal in the original sample. More recent research went further: formulas that assign equal weights to all the predictors are often superior, because they are not affected by accidents of sampling.

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