Posts filed under General (3156)

Team Ratings for Round 12

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 67 matches played, 41 of which were correctly predicted, a success rate of 61.2%.

Here are the predictions for last week’s games.

Predictions for Round 12

Here are the predictions for Round 12. 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.

Justice edition

• From the BBC, a historical story about DNA evidence incriminating someone who had been dead for three weeks at the time of the crime.  Even with modern techniques, the upper bound on the strength of DNA evidence is incompetence or fraud (which has happened) rather than random false matches (which may not ever have happened with good samples)

• A new research paper argues that 4% of those sentenced to death in the US would have their convictions overturned if they waited long enough.  That’s not the same as 4% of them being innocent, but it’s still a problem.

• It’s hard to estimate the role of luck in success, because luck isn’t controllable. Ed Yong writes about a new paper where researchers experimentally randomised people to be lucky, and how much it mattered.

If you ask people in the US to estimate the income of someone at the 80th percentile, they underestimate it, thus underestimating income inequality (PDF).

However, if you specify a dollar amount and ask how many people have income above that amount, you get an underestimate of high incomes.

The take-home message? It’s hard to design good survey questions.

The Herald’s story on birth order and education was nominated for Stat of the Week, which is perhaps a bit harsh.   Here’s the particular sentence (in bold) that attracted criticism, in its context

Eldest children were 7 per cent more likely to aspire to stay on in education than younger siblings and first-born girls were 13 per cent more ambitious than first-born boys, findings from the Institute for Social and Economic Research at the UK’s University of Essex show.

The ‘more ambitious’ is just elongated-yellow-fruit syndrome — it means exactly the same as the ‘more likely to aspire to stay on in education’ earlier in the sentence — not that I’m in a strong position when it comes to criticizing elegance of writing. The researchers used survey data where British kids had been asked at age 13 whether they planned to go into tertiary education, and related their answer to family structure and other variables (PDF).

The sentence in bold is not quite correct — the 13% difference is in the report, but it’s the difference between all girls and all boys averaged over birth order, not between first-born girls and boys. Because of the way probabilities are limited at 100%, the difference between first-born girls and boys will be somewhat smaller, though that’s a pretty technical consideration.  What the figures do make clear is that the difference between first-born and later-born children is quite a bit smaller than the difference between boys and girls.

The Guardian has a similar story, with very similar phrasing, though it’s not clear who borrowed from whom. Where the Herald is different is that the illustrative examples are better. The Herald‘s examples look as though they were chosen, appropriately, from famous Kiwis without regard to birth order; the Guardian has gone in for confirmation bias, choosing famous first-borns.

• via Lennart Nout, a map of where people (well, users of the Strava app) cycle in Auckland.
• Nathan Yau, on the difference in his recorded activities since his son was born.
• Another ‘what you can’t do with big data’ piece, from the New Yorker
• Arbitrary goals can make a difference: many more people finish a marathon just under than just over 4 hours.

How can a sham medical procedure provide huge benefits? And why do we still do them in a world of randomised, blinded trials? Thomas Lumley explores the issue in his latest New Zealand Listener column. Click here.

3 News says “Tests find meth traces in 40pc of houses“.

Now, this is only rentals, but according to the Census there are 563000 rental dwellings in the country, so 40% would be nearly quarter of a million.  If you’re marketing the test as detecting meth labs, this statistic implies either a hugely unrepresentative sample or a test with a high false-positive rate.

In fact it’s probably potentially both. The sample is dwellings where the landlord bought a test from the company MethSolutions, so you’d hope they were higher-risk than average. and the

[MethSolutions] director Miles Stratford told 3 News the results varied from low-level meth use to high-end meth manufacturing.

So the test is picking up both traces of use and unrelated activity in additional to actual manufacture of methamphetamine. Mr Stratford believes [via email to me] that low-level traces of use are still a health risk. I am unconvinced and would count them as false positives, but it’s  not invalid for him to count them as true positives.

[This next quote was about the surveillance product MethMinder, not about the tests: I shouldn’t have conflated them]

“Some of the instances that we’ve found are people using industrial cleaner inside of properties. We’ve had instances where there have been low-grade plastics fires that have produced a whole bunch of volatile gases into the air that have been picked up.”

The company website doesn’t give any information, as far as I can tell, about either the false positive or false negative rate of the tests — they mention Ministry of Health guidelines, but these guidelines are for remediation of known meth labs, not for screening. [Mr Stratford’s subsequent email says that his lab tests have essentially no analytic false positives — ie, if they say there is meth, there is at least some meth present]

And if you’re thinking about using this service you should, of course, read their terms and conditions, which disclaim any guarantees of any level of accuracy, disclose that the service is subsidised by referrals of positive tests to clean-up companies

Where an indicative test is undertaken on behalf of or for the benefit of the owner of a property and that owner or their insurer chooses not to utilise MethSolutions dedicated service providers in quantifying and/or decontaminating and/or reinstating a property, an additional charge of $200 + GST will be due and payable for each of these services that is not utilised but which is required in order to ensure a property is fit to be lived in.

and have other interesting section headlines such as “MethSolutions Is not an Environmental Testing or Security Company” and “No Guarantees on Cost of Sampling.”

Team Ratings for Round 8

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 56 matches played, 29 of which were correctly predicted, a success rate of 51.8%.

Here are the predictions for last week’s games.

Predictions for Round 8

Here are the predictions for Round 8. 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 11

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 61 matches played, 39 of which were correctly predicted, a success rate of 63.9%.

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.

From The Wireless, because that’s where I happened to notice it, not because they did anything wrong

But the average wedding costs about $30,000 – equivalent to a down payment on a house, another comparable goal for a couple in their twenties.

That is the stylised number: you can find it in Stuff and the Herald and lots of other places. But what does it mean? Could it really be true that a typical couple spends about half their annual income on a marriage?

A One News story last year said

Nicky Luis, owner of Lavish Events in Auckland, said while there were no official statistics on the average cost in New Zealand, perceptions within the industry put the figure at $30,000.

That is, people working in the lavish-weddings industry perceive there to be lots of lavish weddings and think it’s normal to spend a lot of money getting married.

Even when the number is supposedly based on surveys there are problems, as Will Oremus wrote last year at Slate

The first problem with the figure is what statisticians call selection bias. One of the most extensive surveys, and perhaps the most widely cited, is the “Real Weddings Study” conducted each year by TheKnot.com and WeddingChannel.com. (It’s the sole source for the Reuters and CNN Money stories, among others.) They survey some 20,000 brides per annum, an impressive figure. But all of them are drawn from the sites’ own online membership, surely a more gung-ho group than the brides who don’t sign up for wedding websites, let alone those who lack regular Internet access.

To make matters worse, the summary quoted from the surveys is the mean, but the way the figure is used, a median would be more appropriate. Oremus extracts the information that  the median is about 2/3 of the mean in those surveys, so we’re getting a 50% increase on top of the selection bias.

When you’re thinking about weddings you’ve been to, there is a different sort of bias. Expensive weddings tend to have more guests, so the average wedding you get invited to is larger than the average wedding you might have got invited to but didn’t.