Stats Chat

Q: Did you see in the Herald that texting doesn’t help relationships?

A: That’s what they said, yes.

Q: And is it what they found?

A: Hard to tell. There aren’t any real descriptions of the results

Q: What did they do?

A: Well, a couple of years ago, the researcher had a theory that “sending just one affectionate text message a day to your partner could significantly improve your relationship.”

Q: So the research changed her mind?

A: Sounds like.

Q: That’s pretty impressive, isn’t it?

A: Yes, though it doesn’t necessary mean it should change our mind.

Q: It sounds like a good study, though. Enrol some people and regularly remind half of them to send affectionate text messages.

A: Not what they did

Q: They enrolled mice?

A: I don’t think there are good animal models for assessing affectionate text messages. Selfies, maybe.

Q: Ok, so that publicity item about the research is headlined “Could a text a day keep divorce away?”

A: Yes.

Q: Did they people about their text-messaging behaviour and then wait to see who got divorced?

A: It doesn’t look like it.

Q: What did they do?

A: It’s not really clear: there are no details in the Herald story or in the Daily Mail story they took it from.  But they were recruiting people for an online survey back in 2014.

Q: A bogus poll?

A: Well, if you want to put it that way, yes. It’s not as bogus when you’re trying to find out if two things are related rather than how common one thing is.

Q: <dubiously> Ok . And then what?

A: It sounds like they interviewed some of the people, and maybe asked them about the quality of their relationships. And that people who didn’t see their partners or who didn’t get affection in person weren’t as happy even if they got a lot of texts.

Q: Isn’t that what you’d expect anyway? I mean, even if the texts made a huge difference, you’d still wish that you had more time together or that s/he didn’t stop being affectionate when they got off the phone.

A: Pretty much. The research might have considered that, but we can’t tell from the news story. There doesn’t even seem to be an updated press release, let alone any sort of publication.

Q: So people shouldn’t read this story and suddenly stop any social media contact with their sweetheart?

A: No. That was last week’s story.

As you know, Leicester City won the English Premier League this week. At the start of the season, you could get 5000:1 odds on this happening. Twelve people did.

Now, most weeks someone wins NZ Lotto first division, which pays more than 5000:1 for a winning ticket, and where we know the odds are actually unfavourable to the punter. The 5000:1 odds on their own aren’t enough to conclude the bookies had it wrong.  Lotto is different because we have good reasons to know that the probabilities are very small, based on how the numbers are drawn. With soccer, we’re relying on much weaker evidence.

Here’s Tim Gowers explaining why 5000:1 should have been obviously too extreme

The argument that we know how things work from following the game for years or even decades is convincing if all you want to prove is that it is very unlikely that a team like Leicester will win. But here we want to prove that the odds are not just low, but one-in-five-thousand low.

Professor Gowers does leave half the question unexamined, though

I’m ignoring here the well-known question of whether it is sensible to take unlikely bets just because your expected gain is positive. I’m just wondering whether the expected gain was positive.

• Interactive exploration of colours used to label subway lines around the world

• A historical list of data visualisations, starting in 5500BCE Mesopotamia

• An example of rainbow colour scales actually misleading people

• Selection bias: @_OneRandomTweet retweets one random tweet every few hours, “to remind you that people don’t use Twitter like you do“

• New Zealand used to have open data on road crashes. Richard Law writes about why getting rid of it was bad.

• Richard Clark: “The boundaries of New Zealand suburbs and localities is held by the New Zealand Fire Service. For years, the NZFS has refused to provide this data under any terms except a restrictive license, and it has to stop.“

• Outsourcing: Andrew Gelman is disappointed in the NZ Herald, so I don’t have to be.

• Survivor bias:

pic.twitter.com/3LS7yH8adC

— Persian Rose (@PersianRose1) April 24, 2016

Team Ratings for Round 11

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 78 matches played, 53 of which were correctly predicted, a success rate of 67.9%.
Here are the predictions for last week’s games.

Predictions for Round 11

Here are the predictions for Round 11. 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.

Team Ratings for Round 10

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 72 matches played, 40 of which were correctly predicted, a success rate of 55.6%.
Here are the predictions for last week’s games.

Predictions for Round 10

Here are the predictions for Round 10. 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.

From NewsHub: “NZ’s most violent city spots revealed”

The approximately one square kilometre grid follows part of Queen St and includes the area around the Sky Tower and casino, as well as the eclectic entertainment strip of Karangahape Rd.

Last calendar year 550 people were the victims of assaults, sexual attacks and robberies in this area.

That’s a rate for these violent crimes more than six-and-a-half times the national average.

The other top locations included two more areas in central Auckland, and a chunk of central Wellington including Cuba St and Courtenay Place.  One thing these four (and quite possibly some of the other top locations) have in common is that a lot of people who don’t live there spend time there — and some of these people commit or suffer violent crimes.  Auckland Central West has a very high violent crime rate for its local population, but some of that is because the relevant population isn’t just the local residents, it’s workers by day and revellers by night.   The area is presumably more dangerous than the national average, but it’s not six and a half times more dangerous.

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 May 6 2016.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of April 30 – May 6 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…)

Q: Did you hear that Auckland housing affordability is better now than when the government came to office?

A: No. Surely not.

Q: That’s what Nick Smith says: listen, it’s at 4:38. Is it true?

A: Up to a point.

Q: Up to what point?

A:  As he says, the Massey University Housing Affordability Index for February 2016 is lower than it was for November 2008, for Auckland and everywhere else in the country. For Auckland it was 38.44 then and is 33.8 now.

Q: But The Spinoff says one of the people behind the Index says Nick Smith is wrong, that housing isn’t more affordable than it was then.

A: Indeed she does. That’s because housing isn’t more affordable.

Q: But you said the index was lower?

A: Yes, it is.

Q: And lower is supposed to be better?

A: Yes.

Q: But how can the Housing Affordability Index be lower when housing isn’t more affordable? What is the index?

A: If it’s the same as it was is 2006 (which would make sense) it’s median selling price multiplied by a weighted-average interest rate and divided by the mean individual weekly earnings.

Q: Can you translate that?

A: Roughly,  the number of weeks of average earnings you’d need to pay the first year’s interest on a 100% mortgage.

Q: So if it’s 34, and you’ve got two people making the average, it’s 17 weeks each out of 52 going to mortgage interest? About 32% of income?

A: That’s right, only you don’t get 100% mortgages, so it’s more like 26% of income. And there’s taxes and insurance and you actually pay off a bit of the principal even in the first year, so it’s more complicated. But it’s a simple summary of the interest cost.

Q: And that’s lower now than in November 2008?

A: So it seems. I wasn’t living in New Zealand then, but it looks like mortgage interest rates were near 9%. The combination of the increase in incomes and the fall in interest rates has been slightly more than the increase in house prices, even in Auckland.

Q: But what if rates go back up?

A: Then a lot of houses will retroactively become much less affordable.

Q: And what about saving for down payments? That’s what all the snake people have been complaining about, and low interest rates don’t help there.

A: Down payments don’t go into the affordability index

Q: But they go into actual affordability!

A: Which is presumably why the Minister was talking about the affordability index.

From the IMF, using OECD data, (via Sam Warburton)

Bar charts should start at zero (and probably shouldn’t  have distracting house/arrow/tree reflections in the background), but this graph would look even worse if the y-axis went down to zero. The problem is that ‘zero’ isn’t 0 for this sort of measurement.  The index is the price:income ratio now, divided by the price:income ratio in 2010, multiplied by 100.  The “no change” value is 100, which suggests using that for the floor of the bars.  Making the bars wider relative to the spaces gives easier comparisons and makes the graph less busy.  The colour scheme isn’t ideal for dichromats, but it only reinforces the information, it’s not needed to interpret anything.

The next step, as Sam suggested on Twitter, would be to give up on the ‘index’, which is really economist jargon, and just describe the change in %.  He also suggesting putting the two labels in colour (which required some fiddling: for the text colour to look like the bar colour it has to actually be darker).

One might also go back to the full names of the countries, but I quite like the abbreviations.

Most of Auckland is within walking distance of a school: there are over 500 schools in the 560 km² of Auckland’s urban area. That’s usually regarded as a Good Thing, and Healthy. Auckland Transport’s “walking school bus” program takes advantage of it to get kids more active and to get cars off the roads. The coverage is pretty impressive: in this map by Stephen Davis, the circles show a 800m (half-mile, 2 km² ) area around each school:

However, as a story at Stuff notes,  if most everywhere in Auckland is close to a school, the schools are going to be close to other establishments.  With a school on most square kilometres of urban land, there will be shops in the square kilometre around most schools selling fast food, or junk food.

That’s going to be even more true in denser, more walkable cities elsewhere, from Amsterdam to New AmsterdamYork.  “Near schools” isn’t a thing in cities. To reduce the number of these shops near schools, you have to reduce them everywhere.

This isn’t to say that all restrictions on fast-food sales are unreasonable, but having lots of things in a relatively small area is hard to avoid in cities. It’s how cities work.