If I would sum up this book in a short sentence it would be "numbers don't like but liars use numbers".
It's a class on data interpretation, and how biased or deceitful charts and graphs can be without the proper context.
Not a fun read, but eye-opening. A 4-star rating on my GoodReads.
Here are my highlights:
- (On sword swallowing) "Young doctor, don't you know that the throat is flat? You can only slide flat things down there. That is why we use a sword".
(p.2) - There is no gap (between rich and poor countries). Today, most people, 75%, live in the middle-income countries.
(p.28) - We almost always get a more accurate picture by digging a little deeper and looking not just at the average but at the spread: not just the group all bundle together, but the individuals. Then we often see that apparently groups are in fact very much overlapping.
(p.42) - More bad news is sometimes due to better surveillance of suffering, not a worsening world.
(p.74) - People often glorify their early experiences, and nations often glorify their histories.
(p.74) - Now that parents have reason to expect that all their children will survive, a major reason for having big families is gone.
(p.92) - (On graph shapes) Don't assume straight lines. Many trends do not follow straight lines [...]. No child ever kept up the rate of growth it achieve in its first six months, and no parents would expect it to.
(p.100) - Critical thinking is aways difficult, but it's almost impossible when we are scared. There's no room for facts when our minds are occupied by fear.
(p.103) - The world seems scarier than it is because what you hear about it has been selected - by your own attention filter or by the media.
(p.123) - "I had for some time been appalled by the systematic blaming of climate change on China and India based on total emissions per nation. It was like claiming that obesity was worse in China than US because the total bodyweight of the Chinese population was higher than of the US population.
(p.140) - Whether measuring HIV, GDP, mobile phones sales, internet users, or CO2 emissions, a per capita measurement will almost always be more meaningful.
(p.141) - "When I see a lonely number in a news report, it always triggers an alarm: What should this number be compared to? What was that number a year ago? Ten years ago? What is it in a comparable country or region? And what should it be divided by? What is the total of which this is a part? What would this be per person? I compare the rates, and only then do I decide whether it really is an important number".
(p.142) - Compare: big numbers always look big.
(p.143) - When something goes wrong don't look for an individual or a group to blame. Accept that bad things can happen without anyone intending them to.
(p.222) - Give the system some credit. When someone claim to have caused something good, ask whether the outcome might have happened anyway, even if that individual had done nothing.
(p.222)
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