Noise
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Gesprochen von:
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Todd Ross
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Daniel Kahneman
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Olivier Sibony
‘Noise may be the most important book I've read in more than a decade. A genuinely new idea so exceedingly important you will immediately put it into practice. A masterpiece’
Angela Duckworth, author of Grit
‘An absolutely brilliant investigation of a massive societal problem that has been hiding in plain sight’
Steven Levitt, co-author of Freakonomics
From the world-leaders in strategic thinking and the multi-million copy bestselling authors of Thinking Fast and Slow and Nudge, the next big book to change the way you think.
We like to think we make decisions based on good reasoning – and that our doctors, judges, politicians, economic forecasters and employers do too. In this groundbreaking book, three world-leading behavioural scientists come together to assess the last great fault in our collective decision-making: noise.
We all make bad judgements more than we think. Noise shows us what we can do to make better ones.
Kritikerstimmen
New York Times
Sunday Times
Martha Gill, Evening Standard
Esther Duflo, winner of a 2019 Nobel Prize
Philip E. Tetlock, co-author of Superforecasting
David Lammy
However, I’m unhappy with the narrator. The stress of the voice is often at parts of the sentence that I would consider less important. I need to concentrate a lot to rearrange the parts in my mind to be coherent. Also, this is a non-fiction book that not only contains continuous text. There are several sub-headings and at the end of the chapter important quotes; none of those are clearly seperated by voice.
In a similar vein: Why am I forced to rate the story of this book in order to write my review? That does not apply to non-fiction texts at all.
More insights into human thinking
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The whole book can be summarized as "there's a much larger variance in decisions that we expect to be rather accurate", be it judges giving sentences or doctors deciding treatment. The examples are in fact well chosen and a little bit jaw-dropping, but I couldn't look past this erroneous use of perfectly fine mathematical terms.
I also feel like the authors stressed MSE too much, there are also other metrics. They did mention that in the middle and in the end, but failed to stress that for other accuracy cannot in general be split into bias squared + variance
Why did they rename "variance" to "noise"?
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Brilliant and important book
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Informative but hard going
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Excellent
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