Rob Minto

Sport, data, ideas

Month: July 2011

How to live dangerously – a book that does statistics a disservice

Being a statistics junkie, a couple of people recommended to me the book How to live dangerously by Warwick Carins. Normally, I would read it, enjoy, and move on. But this book has prompted a mini-review (several years late, but who cares…), because it commits several statistical crimes.

One is that Cairns plays fast and loose with surveys. Surveys here, surveys there. No mention of how many people asked, by which method, or the sources. We can all cherry pick surveys to prove any point we like. A health warning is needed.

Second, Cairns is too casual to dismiss what we don’t know, and uses little data to back up the main thrust of the argument (which I broadly agree with), peppering his prose with “probably”s and “these days”. Example:

In 1970, eight out of ten elementary schoolchildren used to walk to school. In 2007, less than one out of ten did – and they were probably the ones who lived across the road, or whose dads were the school caretakers. Most children these days are driven to school in cars, even if they live just round the corner.


Thirdly, and far worse, it actually uses statistics to deceive, rather than prove a point. The worst offence is comparing the data on child abduction and murder with death from fires.

It is clear that the media make more of the former than the latter – a child killed in a fire is a tragedy that is maybe mentioned in the local news, while an abduction and murder will make national headlines quite often.

But Cairns breaks down the stats by pointing out that in any one year, only 100 or so US children are abducted by strangers, and of those 46 are killed. He then extrapolates that to say that the average child has a 0.00007 per cent chance of this fate, which equates to it taking 1.4m years for a stranger to murder your child if you left him or her unguarded on the street.

Obviously the idea of living for 1.4m years is nonsense, and a cunning way of pointing out our ridiculous fear of this event. But then he points out the relative danger of keeping a child indoors and the risk of fire, to show how foolish we are at stopping children going out.

Not citing which country (I assume the US again) he says “one child dies of [fire in the home] every ten days.”

So he sums up our fears thus (from p46):

So, they go out, and face the 1-in-1.4 million chance of being abducted and murdered. Or they stay in, where one child gets burned to death every ten days.

This is the worst statistical argument I have ever come across. Comparing a 1-in-1.4m chance (which is not the same as 1-in-1.4m years anyway) with one-in-10 days sounds like a logical slam dunk – why on earth would we care about the million chance when every 10 days a child dies in a fire? Except that these are far more similar stats than the way they are presented. Actually, using Cairns’ data, one child is abducted and then murdered every 8 days, compared to a death every 10 days in a fire. Or, put it another way, there are 46 abductions and murders every year in the US compared to roughly 37 fire deaths.

Either Cairns is being appallingly deceptive, or incredibly sloppy and can’t understand the stats himself. Either is hard to forgive in a book that tries to cut through the froth and present our fears and risk in a rational way.

Overall – for a book that cites statistics and tries to uncover our irrational fears, it is sloppy, prejudiced and patronising. It is poorly sourced, and although entertaining, lacks rigour. This is an important topic. It’s a shame that it is treated so badly.

Secret winning formula: high fives

Apparently giving high fives makes you a winning team! High Five!

You don’t have to be sport’s answer to Ben Goldacre to realise that it might be something to do with winning in the first place that makes people high five, rather than the other way about.


  • Why fist-pumps make you a tennis champion
  • Why a propensity to stand on podiums and spray people with Champagne makes you a winning race driver
  • Gatorade: tip it over your manager for best results
  • Why that weird running-hands-together-and-dive-on-the-pitch celebration will win you football silverware

The gender timebomb of India and China: a stab at the numbers

When I visited India in 2003, I was shocked by areas of the countryside where there seemed to be not a young girl in sight. It was all boys, as far as you could see.

When we asked our tour guide about the lack of girls, he scoffed at any suggestion of infanticide or selective abortion. Instead, he told us that women could conceive a boy if they slept on a particular side of their body just after intercourse.

This was a man with a degree, a full education and seemingly worldly-wise. He surely couldn’t believe the old-wives tosh, and was just peddling nonsense to avoid reality.

But the population time-bomb in India and China is soon going to be upon us. China pursued a one-child policy that has skewed a generation towards males. India’s gender imbalance is cultural rather than state-imposed, but has a similar effect.

Take India. If the 917 girls to 1000 boys ratio is correct, that means by 2020, we are looking at over 25m (and probably closer to 35m) shortfall in girls to boys in a 15 year generation.

The back-of-envelope maths:
There are 100m plus children aged 0-4. Multiply by 3 for a 15-year generation. 300m * (1-0.914) = 25.4m

In other words, there are going to be, in all likelihood, over 20m young men in India who have no chance of finding a partner.

In China, it’s around the same scale – over 20m young men left out of the dating game. The population data used in the CIA Factbook bears this out:

0-14 years Male Female Difference
India 187,450,635 165,415,758 22,034,877
China 126,634,384 108,463,142 18,171,242

In a generation, we are going to have over 40 million enforced bachelors in India and China. What does this mean for these societies? There are several trends we can expect, as outlined in Bare Branches:

high male-to-female ratios often trigger domestic and international violence. Most violent crime is committed by young unmarried males who lack stable social bonds. Although there is not always a direct cause-and-effect relationship, these surplus men often play a crucial role in making violence prevalent within society. Governments sometimes respond to this problem by enlisting young surplus males in military campaigns and high-risk public works projects. Countries with high male-to-female ratios also tend to develop authoritarian political systems.

In other words:
– rising crime in sex trafficking and prostitution
– social bonds weaken
– riots and disillusionment
– authoritarian crackdown
– high military enrollment

Not a wildly happy future. All those who see India and China as a one-way bet should perhaps think again.

Further reading:

BBC:India’s unwanted girls
Economist: The worldwide war on baby girls
Economist: China’s population – The most surprising demographic crisis
UNFPA: Sex-Ratio Imbalance in Asia: Trends, Consequences and Policy Responses

UPDATE: The economist has a great chart on China’s population and the impact of the one-child policy.

The crazy world of Wimbledon’s prize money

In a good but not great Wimbledon final, Novak Dkokovic beat Rafael Nadal today. I was supporting Nadal (actually I am quite a big Nadal fan). So I did what you might call an “emotional hedge” and put a bet on Djokovic to win.

Some people see this as heresy. I’m not sure why. For no moment did I stop supporting Nadal. But after the match had finished, I thought – hey ho, cheer up, you made a few bob.

So my mood was altered. Here’s the e-ticket from BlueSquare:

Selection 1 Novak Djokovic @ 5/4 To Win – Win
Market Match Winner
Event Wimbledon
Rafael Nadal v Novak Djokovic
14:05 03/07/2011
Bet Type Single
Unit Stake £40.00
Returns £90.00

Very nice. Not bad odds either, for a 2-horse race, where the outsider had only lost one match all year. So a £50 return improved my mood. Not a fortune, but a decent sum for a small wager.

And then I thought – what about Nadal? Is he happy? I doubt it. He has lost the title, and the number one ranking to Djokovic. I’m sure he’s not having a crisis, but he certainly won’t be happy. Yet he’s just earned £550,000 today as runner up.

That’s 11 thousand times my winnings today. He’s definitely not 11,000 times happier than me, that’s for sure. Yes, it’s all relative. But I think Nadal would be unhappy today if he got £2 million of even £20 million. His game is now measured in titles, not money. He’s already earned over $41m in prize money alone, let alone sponsorship, so he’s set for life.

Which leads me to two thoughts. Money doesn’t make us happy – we all knew that really, so let’s move on to… why are sportspeople paid so much? And so much more than inflation? Nadal as runner up has just won more money than Lleyton Hewitt did in 2002 – less than 10 years ago. (Hewitt got £525,000 for winning, Djokovic just got £1.1m today).

Wimbledon has increased prize money this year by 10 per cent for most stages of the tournament (including winner and runner up), and by 8.5 per cent overall. This is much higher than inflation. Why do they need to do it?

Is there a prize money race with other events? Does prize money equal prestige? Hardly. Other tournaments offer a lot, but you would have thought the grand slams – which have a joint committee – would conspire not to push up prize money too high.

It also seems horribly similar to the corporate world, where CEO pay is many multiples of average workers. The winner earns eight times a losing quarter-finalist. I see the logic in halving the money as you go down the field, but a quarter-finalist has won four matches, compared to the winner’s seven – more than half the entertainment and effort for 1/8th of the money.

Is this fair? No. Would the winner be happy with a fraction of the winnings? Yes, I’m sure. So why don’t we change? Why isn’t the money more evenly spread around. It would be interesting to see which players kicked up a fuss.

But then again, I’m quietly chuffed with my £50 winnings. It’s funny what a little money can do.

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