Posts from June 2016 (41)

Team Ratings for Round 16

The basic method is described on my Department home page.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 111 matches played, 65 of which were correctly predicted, a success rate of 58.6%.
Here are the predictions for last week’s games.

Predictions for Round 16

Here are the predictions for Round 16. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday June 24 2016.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 18 – 24 2016 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

Two more news sites have fallen for the cheese addiction story.

A recap for those who missed the earlier episodes:

• There was a paper using the Yale Food Addiction Scale that evaluated a lot of foods for (alleged) addictiveness.
• Pizza came top.
• Someone (we don’t know who) pushed a story to various media sites saying the research had found cheese-based foods were the most addictive (false), and that this was because of milk protein fragments called casomorphins (which aren’t even mentioned in the research paper, as you can check for yourself, and which haven’t been shown to be addictive even in mice).
• The people behind the research have disclaimed these weird interpretations of what they found. Here’s a detailed story

In a Herald (Daily Telegraph) story this week

When confronted, he confessed he’d been having an affair with a single mother he met at the school gates.

“She was vulnerable,” says Janet. “I guess he liked that. It made him feel like a hero.”

Her experience sadly chimes with the findings of a new study of more than 2,750 young married people by the University of Connecticut, which showed that men who are financially dependent on their spouses are the most likely to be unfaithful. In fact, the bigger the earning gap, the more likely they are to have an affair, with those who rely solely on their wives for their income the biggest cheats.

It turns out there are things wrong with this story, even restricting to statistical issues. To find them, you’d need to look at the research paper, which you probably can’t, because it’s paywalled.  I should note that these aren’t necessarily all criticisms of the paper for the question it was answering (which was about motivations for fidelity/infidelity). but they are for how it has been used — to turn a couple of anecdotes into a Deeply Worrying Social Trend.

First, the income data. The researcher writes

I calculated the measure from respondents’ and their spouse’s total income earned during the previous year from wages, salaries, commissions, and tips. I excluded self-employment income, because the division between labor income and business income is often measured with substantial error.

That means the group described as ‘rely solely on their wives for income‘ includes all the self-employed men, no matter how much they earn. There may well be more of them than voluntarily unemployed house-husbands.

Second, a somewhat technical point, which I think I last covered in 2012, with two posts on a story about mid-life crisis in chimpanzees.

Here’s a summary of the model given in the research paper

Notice how the curved line for men bends away from the straight line for women on both sides? And that the deviation from a straight line looks pretty symmetric? That’s forced by the statistical model.

Conceptually, the left and right sides of this graph show quite different phenomena. The right side says that the decrease in infidelity with higher relative income flattens out in men, but not in women. The left side says that the increase with lower relative income accelerates in men. The model forces these to be the same, and uses the same data to estimate both.

Since there are more men with positive than negative relative income, most of the actual evidence for men is on the right-hand side, but the newspaper story is looking at the left-hand side.

A Herald story, under the headline Selfies can damage your health

Dermatologists now believe that regularly exposing the face to the light and electromagnetic radiation from smartphones can speed up ageing and wrinkles.

The people making that claim don’t seem to be giving any evidence. You’d need a lot of evidence to believe a claim like that, given how much more light and electromagnetic radiation we get from the sun. Sure, sunlight doesn’t have quite the same frequency spectrum, but it’s so much brighter that it will be giving you more exposure at any frequency.

Also, when you’re taking selfies, your phone is usually not particularly close to your face.  After all, that’s why selfie sticks were invented. If the claim were true, the real message would be that selfies protect your health.

Doctors even claim they can tell which hand a person holds their phone in just by looking at which side of the face is most damaged.

I have no real doubt that this doctor can tell which hands his patients hold their phones in — for example, by observing what hand they use for other things, or what pocket the phone is kept in.  But, again, people nowadays don’t spend much time holding their phones up to one side of their faces. You only do that for phone calls, and only then if you don’t have a headset, and that’s such a twentieth century way to use a phone.

And, yes, the people involved are all selling something.

(This story comes from the Daily Telegraph, though it didn’t say so when I first read it, and according to a credible witness it said Daily Mail earlier)

From the Herald

According to a new study by computer scientists at Columbia University and the French National Institute, 59 per cent of links shared on social media have never actually been clicked: In other words, most people appear to retweet news without ever reading it.

Perhaps appropriately, the Herald passed on this story from the Washington Post without passing on their link to the research.

If you were reading carefully, you might notice the last part of the paragraph doesn’t actually fit the rest: it isn’t that ‘most people‘ retweet news without ever reading it, it’s that most retweets are done without reading (or before reading).  Even with that caveat, the research says that headlines matter — and I’m going to keep complaining about them.

The main focus of the research was something different, though. They were comparing clicks on the ‘primary’ URLs from the media site itself with the clicks on shortened URLs produced by readers.  Although the primary URLs had the majority of ‘impressions’, the secondary URLs added up to more clicks.  That is, when news stories are actually read via Twitter, more often than not it’s because of a personal recommendation by someone else who has actually read the story.

• Randomized controlled trial of police foot patrols, near Cambridge.

• How the Financial Times does data visualisation

• An interview with economist Claudia Goldin on the mechanisms behind the gender pay gap

• Harkanwal Singh from the Herald, talking at the NZ Open Data showcase

• The impact of open data on cities.

• The six-year war for NZ weather data (Philip Duncan isn’t unbiased on this, but he knows what he’s talking about)

So, there’s a new IARC cancer monograph out, but this one is disappointingly un-scary. (Here’s the Q&A)

There are two basic points. First, coffee looks safe. Officially it’s “inadequate evidence”, but that basically means “if we were in the business of calling things ‘safe’, coffee would be on the list”.  There has been enormous effort over decades to find health risks of coffee for all sorts of diseases, with extremely limited success. Coffee can make it harder to fall asleep, and that’s about it.

The second point is about ‘very hot drinks’. These are listed as ‘probably carcinogenic’, meaning there’s some evidence that regular consumption increases the risk of oesophageal cancer  (not that you’ll probably get cancer if you drink them).  By ‘very hot’, they mean very hot,  over 65°C when consumed, which is relatively unusual in New Zealand.  Here, it’s alcohol and smoking that are the main risks for oesophageal cancer.

The Immigration Minister, Michael Woodhouse, was on RadioLive

Per capita, New Zealand is ranked about 90th in the world for the number of refugees it accepts. Mr Woodhouse says this low ranking isn’t the Government’s fault — its quota puts New Zealand at “about seventh or eighth”. It’s refugees turning up unannounced that puts other countries ahead — like Jordan taking in refugees from the Syrian civil war, for example.

“I don’t want to get into a game of statistics, but we can be pretty pleased with what. We can say seventh, you can say 90th.”

When you have answers that differ that much, it’s either because someone has the numbers wrong, or (as in this case) because they are answers to different questions. When you have answers to different questions, the right statistical approach isn’t to look at the answers and decide which one you like, it’s to look at the questions and ask which is the right one.  That is, should we regard refugee numbers as basically about resettlement quotas managed through UNHCR, or as including asylum seekers?

People setting off on their own into neighbouring countries is, has always been, and probably always will be the main way they become refugees. The refugee resettlement process is a way for countries who aren’t within walking/driving/sailing distance of a humanitarian disaster to contribute and to perform some of their duty to the international community.  But the refugees who turn up unannounced, not the tidily resettled ones, are the primary and usual case. They should be included in the count unless there’s some special reason occasionally not to.

New Zealand doesn’t accept many refugees — and most countries probably wouldn’t if they could avoid it. Germany and Turkey are currently handling very high numbers because of asylum seeker fleeing the Syrian crisis, but had much lower numbers ten years ago. But German and Turkey really are accepting more refugees now. If you were in Mr Woodhouse’s ‘game of statistics’ and you were handed the ‘no, nothing has changed much’ side of that argument, you would lose.

New Zealand accepts a very low number of refugees either per capita or per unit GDP.  Some people are happy with that. Many people, probably, are happy that it’s not ten or twenty times larger, as in several European countries. But it is a very low number and people who don’t want it to change should be honest about that.

In any case, whether we count qualifying asylum-seekers or just resettled refugees, whether we look per capita or per dollar of GDP, there’s one consistent finding. We accept fewer refugees than Australia.