
Forecasting is a talent – luckily it can be learned - edward
http://www.economist.com/news/books-and-arts/21666098-forecasting-talent-luckily-it-can-be-learned-unclouded-vision
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nl
I took part in the last round of the Good Judgement Project, and finished top
20. I also work in the field (although around more specific incident
forecasting than the GJP worked in).

I think the points made in the book (and on the GJP blog[1]) are useful. The
idea of trying to put probabilities around your assumptions is pretty useful
for example.

The other lesson I learnt was that predicting things to stay the same is
generally a safe bet. Often the challenge is working out which side of a
prediction require less things to change.

If you are interested in the details, [2] is a pretty good overview.

[1] [http://goodjudgment.com/gjp/](http://goodjudgment.com/gjp/)

[2]
[http://www.nesta.org.uk/sites/default/files/1502_working_pap...](http://www.nesta.org.uk/sites/default/files/1502_working_paper_-
_prediction.pdf)

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quietplatypus
They make it sound simple: apply a rational, scientific mindset to life. Talk
about easier said than done. Most of us sink into easy-to-reach reactions that
are only good for the simplest situations, and sometimes not even then, and
often come with emotion or resentment. Still, the former mindset is a nice
ideal to shoot for.

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copperx
I have an honest question. If I believe that I would make an incredible
forecaster, where can I start testing myself? Is there something that requires
significant less amount of information before starting to forecast, than, say,
stocks?

~~~
roymurdock
[https://www.kaggle.com/](https://www.kaggle.com/)

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MarkMc
Is there a public list of answers provided by the 'superforecasters'?

For example, I would love to know the average superforecaster's answer to "How
much will China's economy grow over the next 10 years?"

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MarkMc
I would love to know whether the distribution of 'superforecasters' on the
political spectrum is much more narrow than the general population.

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sparkempire
interesting

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source99
Did not read the article.

All skills can be learned and there is no such thing as natural talent for a
specific skill set.

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SixSigma
Except that's not entirely true and a few minutes thought should convince you
that some people are better at playing the piano than others, even after years
of practice.

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source99
I've read a number of studies that contradict your statement. They say that
the ONLY thing that matters is the amount of practice and natural skills play
no part in level of mastery.

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SixSigma
Try watching Dancing with The Stars

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dragonwriter
I assume that that's intended as a reference to a simple method of
_disproving_ the contention that _only_ practice time matters.

(It certainly supports the idea that practice time on the specific task
matters -- which is noncontroversial -- but it doesn't support the idea that
practice time _alone_ determines performance.)

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SixSigma
The show demonstrates that some people are inherently better at tasks
requiring physical dexterity, timing and grace. Can you teach those things?

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fuzzieozzie
I forecast this comment will NOT make it to the top of the comments!

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aynsof
Here's an experiment: get a million people to guess the results of a thousand
coin-tosses. By the end, a miraculous few will have a 100% record and will be
hailed as geniuses. Books will be written about this incredible group. These
books will find the traits that, by chance, the group members happen to share
with each other. ("My god, they all have brown hair!" "Yes, but they come from
eclectic backgrounds - housewives, factory workers, math professors." "How
fascinating!") But what is the probability any one member of that group
correctly guessing the result of the _next_ coin toss?

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crimsonalucard
you get one person to guess the result of 1000 coin tosses that's a 1/(2^1000)
probability of one person being right. Get a million people to guess it it's
(10^6)/(2^1000) probability of one person being right.

Lets put it in perspective; the chance of one person out of a million getting
a 100% streak is 9.332 × 10^-296 %. That's significantly less than
0.000000000000000000000000001%.

If there are people who have a 100% record of being correct on every guess,
the probability of them being geniuses is way higher than the probability of
them being lucky.

That being said, I get your point. We don't have enough metrics from the
research to determine whether or not these super forecasters are just lucky or
geniuses.

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grayclhn
It turns out not to matter (since the numbers are so small) but your math
implies that 10^305 people guessing would give a probability of about 9,300
that at least one of them is right on all 1000 coin flips. Since probabilities
can't be larger than 1, that's a bit of a problem.

For anyone interested, the full set of steps (that produces a numerically
identical result):

    
    
        Prob[1 or more in 1,000,000 right]
          = 1 - Prob[all 1,000,000 wrong]
          = 1 - Prob[person 1 is wrong AND person 2 wrong AND ... person 1,000,000 wrong]
          = 1 - Prob[person 1 is wrong]^1,000,000
          = 1 - (1 - 0.5^1000)^1,000,000
          = 1 - exp(1,000,000 * log(1 - 0.5^1000))
          = 1 - exp(1,000,000 * log1p(-0.5^1000))
          ≈ 1 - exp(1,000,000 * -9.33 × 10^-302)
          = 1 - exp(-9.33 × 10^-296)
          = -expm1(-9.33 × 10^-296)
          = 9.33 × 10^-296
    

log1p(x) = log(1 + x) but is more accurate when x is near zero.

expm1(x) = exp(x) - 1 but again is more accurate when x is near zero.

Both are necessary here to get a result other than "0".

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SamReidHughes
It's perfectly reasonable to approximate a+b=a+b(1-a) when combining rare
events without announcing it to everybody. Likewise with n repetitions of
that.

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grayclhn
Fair enough, but it's also reasonable to approximate 9.33 × 10^-296 as 0. I
felt like doing the calculations :)

