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How Not to Be Wrong: The Hidden Maths of Everyday Life Paperback – 26 May 2015
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1. Survivorship bias – average return on investment funds for example - omits the funds that were so unsuccessful that they were closed – so that only survivors data is analyzed resulting in a false impression;
2. Sometimes a line is actually a curve or a parabole. About the risks of linear regression (continuous increase of population is not a straight line but a curve so that the expected rate of growth will be reduced);
3. A small selection will produce more unexpected results – for example smaller population states have the most extreme ratios for cancer – both low and high – but this is just another result of randomness and does not give any important insights;
4. Law of large numbers revisited from several angles;
5. Don’t talk about percentages of numbers when the numbers can be negative. The example is job growth by sectors – lets say retail sector adds 10 jobs, construction loses 10 jobs and IT adds 2 jobs. The total job adds are 2 people. So if you would want to manipulate the data you could say that all the jobs were created in the IT sector, because the total job growth is the same as the IT sector growth;
6. There was another warning about getting fooled by randomness: a stockbroker sends different stock tips to a large number of recipients and does this over and over. There will be a few recipients who will get stock tips that were right again and again. So the stockbroker can seem genius because no-one will be able to know about all the wrong suggestions;
7. Bayesian inference. A fancy name in order to impress at smalltalk but basically means a statistical test which is done on the same data but after some new input has emerged;
8. p-values. How to test the reliability of scientific statistical studies. Turns out that there still are many unreliable studies published;
9. There was also a big discussion on the election systems in different countries. Basically the paragraph showed how in many cases the system modifies the initial process in such a way that the most popular candidate may not win.
A few general comments:
1. It is mostly a very boring book and although it contains lots of important intelligence then because of the books marketing I was hoping for much more entertaining read;
2. I made lots of notes in the book but there was a big gap from about page 189 to 272 when it just got too theoretical.
3. Although the book should show us the maths in everyday life it seems to be mostly intended for math scientists in order to show to their kids that their work has some real life connection instead of showing to the rest of us to apply math concepts in real life. Do not get me wrong, it has this value also, but there is just too much of theoretical math.
However, my criticism is aimed at the publishers, not the author. The text is a bit small (I'm in my 40s, and the text is only just about legible), and the asterisks (used for the footnotes) are microscopic. Frequently I would get to the bottom of the page and discover that the author had written a footnote. I would then spend a good minute or two trying to discover where the asterisk was in the text, and then have to do some re-reading to remind myself of the context of what the footnote was for, then finally read the footnote. By which point I had lost the thread of the rest of the page, and would need to re-read that before I could progress.
So rather than be a nice little aside (like you would experience when reading a Terry Pratchett novel), each footnote added about 3 or 4 minutes of discontinuity to the reading.
It's certainly worth a read; just don't try to use it as a substitute for the paperback you'd normally take to enjoy on the poolside lounger at your beach hotel.
Actually it's even more than great. It's understandable.
It talks about complicated topics in a way that everyone can understand.
If only teachers at school would teach math that way :)
It helps you get the real meaning of math. Not the formulas, not the calculations, not the numbers.
The real thing.
Math in every day life.