Stats Chat

From an admittedly bogus poll of my followers on Mastodon

The correct answer is “none of the above”. The most appropriate common name is probably “avocado”

It looks like most respondents didn’t know what Persea americana is, but assumed the question was about some actual controversy such as the appropriate name for Actinidia deliciosa cultivars  — ‘kiwifruit’, but often called ‘kiwi’ in the US. This is frivolous, but it’s similar in many ways to putatively serious survey questions such as “bombing Agrabah” or asking about Harambe as a presidential candidate in 2016.

Team Ratings for Week 2

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 5 matches played, 2 of which were correctly predicted, a success rate of 40%.
Here are the predictions for last week’s games.

Predictions for Week 2

Here are the predictions for Week 2. 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 Week 5

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 20 matches played, 11 of which were correctly predicted, a success rate of 55%.
Here are the predictions for last week’s games.

Predictions for Week 5

Here are the predictions for Week 5. 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 2

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 8 matches played, 3 of which were correctly predicted, a success rate of 37.5%.
Here are the predictions for last week’s games.

Predictions for Round 2

Here are the predictions for Round 2. 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 BBC Somerset: “Rare coincidence as three cousins born on same day“. Two sisters-in-law gave birth on the same day, one to identical twins. One of the hospitals notes that identical twins are about 1 in 250 pregnancies. It’s going to be uncommon for two closely-linked women to give birth to three kids on the same day. The chance increases as you consider non-identical twins and more relationships — primary-school BFF, college flatmate, next-door neighbour, sky-diving partner, whatever.  Given that the UK has over half-a-millon births per year, this has got to be a thing that regularly happens.  It’s still rare enough to properly be a big deal to the families involved, and BBC Somerset aren’t overselling it too much.
• From a BBC news item about electricity theft (and the risks involved)
  
  The clear increase shown in the graph is a bit undermined by “Crimestoppers estimates that a further 250,000 cases go unreported every year”. If 95% of cases are unreported, there’s no hope for estimating trends from the 5% of reported cases — we can’t possibly distinguish trends in reporting from trends in the true rate.  Long-time StatsChat readers will remember me saying this about everything from skin cancer to domestic violence.
• Weight-loss jab could be made for $3 a month, study finds (Guardian).  This is plausibly true and I’m not going to argue that pharmaceutical prices are where they should be. However, as with The Guardian itself, the price of one additional copy of the the finished product is not the main determiner of the price, nor should it be.
• CNN: Here’s how much the war with Iran is expected to cost every day. The answer they give is nearly US$1 billion per day. That’s a lot, but the US is a big country: it’s about three times the US daily spend on coffee and a bit less than the cost of car insurance.  More importantly, it’s not the cost of the war. It’s  not even the cost of the war to the USA as ABC News and Al Jazeera frame the same number. It’s only the cost of the munitions used by the USA.  The cost of the war, under any attempt at reasonable accounting, is far higher.

The Guardian reports “Gen Z males twice as likely as baby boomers to believe wives should obey husbands”, with similar phrasing in headlines from the Daily Mail, and the NY Post, and in the lede from the BBC. This has, unsurprisingly, caused a bit of concern.

Looking at the original information from King’s College London (research for International Women’s Day†) the trend seems to go over all ages

This seems strange. I would not have thought women’s equality had been getting steadily worse for the past eighty years. Do we just have a bad question, or a bad sample, or what? The page at King’s College shows broadly similar patterns for other gender attitude questions, though often less extreme. It’s not just the question but it might be partly the question.  In particular, there might be a carryover from ‘obey’ in wedding vows, which is not quite the same. However, “A husband should have the final word on important decisions made in his home” gets very similar answers to the “obey” question.

Here’s the worldwide comparison for the ‘obey’ question:

There’s a huge amount of variation between countries, so the results will be sensitive to how countries are combined.  Honest and competent researchers will give you this sort of information, and there is a full PDF report actually linked from the King’s College page, near the top!  It has a Technical Note on the last page that says in part

The data is weighted so that the composition of each country’s sample best reflects the demographic profile of the adult population according to the most recent census data. “The Global Country Average” reflects the average result for all the countries and markets in which the survey was conducted. It has not been adjusted to the population size of each country or market and is not intended to suggest a total result. [emphasis added]

It would be interesting to see separate trends for countries and regions, rather than suggesting a total result, when the responses from different countries are so different.

† Yes, there is. November 19.

Newsroom has a long piece on traffic congestion in Auckland in March. Near the beginning, Douglas Wilson, from the Transport Research Centre at the Uni of Auckland says

“So suddenly people say, ‘Wow, it’s taking me double the travel time to get to work. Why is that the case?’ It’s not that you’ve doubled the traffic volume. Actually, the volume has only gone up a little, proportionally, but the traffic flow has reached capacity.”

This is one of the Two Simple Facts from queueing theory, the branch of applied probability that deals with congestion in networks. These networks can be physical road networks or electronic data networks or something like a system of medical waiting lists, or something as simple as a literal queue, and what they all have in common is waiting for other users.

Queueing theory can lead to very complicated simulations and theoretical approximations, but parts of it are simple. My Two Simple Facts are

1. When you have multiple servers you should still try to have a single queue
2. A queueing system has a “capacity” and when it gets near that capacity small changes make things much worse

Most of the time, Auckland’s traffic system works reasonably well. There’s enough wiggle room for traffic to catch up around the inevitable slowdows.  When you get a big crash on the motorway or heavy rain or extra drivers, though, the whole system suddenly gets much slower. In the other direction, removing drivers after Christmas opens up the city out of all proportion to the number who leave.

Sudden slowdowns near full capacity are a pretty general property of queueing systems. We can look at them in a nice simple example — this sort of mathematical model is very useful both for understanding the general vibes and for developing theoretical tools.

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Team Ratings for Week 1

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.

Predictions for Week 1

Here are the predictions for Week 1. 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 18

Not sure how I missed posting this one, but here it is for completeness.

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 119 matches played, 94 of which were correctly predicted, a success rate of 79%.
Here are the predictions for last week’s games.

Predictions for Round 18

Here are the predictions for Round 18. 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 Delayed Games

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 93 matches played, 61 of which were correctly predicted, a success rate of 65.6%.
Here are the predictions for last week’s games.

Predictions for Delayed Games

Here are the predictions for Delayed Games. 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.