Posts filed under General (3152)

Team Ratings for Round 14

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 100 matches played, 59 of which were correctly predicted, a success rate of 59%.
Here are the predictions for last week’s games.

Predictions for Round 14

Here are the predictions for Round 14. 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 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 94 matches played, 66 of which were correctly predicted, a success rate of 70.2%.
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.

Team Ratings for Round 13

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 96 matches played, 57 of which were correctly predicted, a success rate of 59.4%.
Here are the predictions for last week’s games.

Predictions for Round 13

Here are the predictions for Round 13. 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.

• “It is important that guidelines for mitigation measures are proportionate to the risk posed, and that remediation strategies should be informed by a risk-based approach.” That’s not the money quote from Sir Peter Gluckman’s report on methamphetamine testing for houses (PDF), but it’s the generic StatsChat message.  For more, see Russell Brown’s story; he has been a consistent journalistic voice against panic-based testing.
• From an NY Times oped “Knowing a person’s political leanings should not affect your assessment of how good a doctor she is — or whether she is likely to be a good accountant or a talented architect. But in practice, does it?  Recently we conducted an experiment to answer that question”.  As Andrew Gelman explains, they totally didn’t.
• A new UK Parliament report “Algorithms in Decision Making”
• “Why Government needs sustainable [statistical] software, too”

Q: Did you see using a mobile phone after 10pm leads to depression and loneliness, depression, bipolar disorder and neuroticism?

A: Where?

Q: The Independent, the Daily Mail, news.com.au, the Geelong Advertiser, Student Problems, …

A: So, what are we supposed to check first?

Q: Mice. It isn’t mice, it’s people.  “However, now a study of more than 91,000 people has found that scrolling through your Instagram and Twitter feeds from the comfort of your pillow in the wee hours could increase the likelihood of developing a number of psychological problems such as depression, bipolar disorder and neuroticism.”

A: Ok, ok.  Do any of them link?

Q: The Independent does. But it’s behind a paywall

A: <sighs> Ok. Here’s the press release. 

Q: But that doesn’t mention mobile phones. Or Twitter or Instagram.

A: No, it doesn’t.

Q: It looks like they used fitbits, though

A: Yes, or near offer.

Q: Could they tell from those when someone was using their phone?

A: I don’t know if they could, but they didn’t. They just looked at how much people’s physical activity differed between night and day.

Q: What’s that got to do with mobile phones?

A: If using your phone late at night stops you sleeping, then you might have less difference in activity between night and day.

Q: I suppose. Did they look at actual sleep?

A: Not in this study

Q: So, the people with less day-night difference in physical activity ended up with more mental health problems?

A: No, they started off with more mental health problems.  As the comment at the bottom of the press release says “The study population (median age at baseline of 62 years, IQR 54-68 years) is not ideal to examine the causes of mental health, given that 75% of disorders start before the age of 24 years.”

Q: These were 60-year olds?

A: Yes. In 2013-14.

Q: Did British 60-year-olds even use Twitter and Instagram in 2013-14? Instagram was only on iPhones back then, wasn’t it?

A: About a third of Brits between 55-64 had a smartphone then, and about 10% of older people.

From Toby Manhire at The Spinoff, quoting Reuters

“New Zealand’s dairy-fuelled economy has for several years been the envy of the rich world, yet despite the rise in prosperity tens of thousands of residents are sleeping in cars, shop entrances and alleyways.”

There was something similar in the Guardian, too. As Toby says

The juxtaposition is compelling and well made. The number is compelling and nonsense.

I’ve posted about this issue before. The OECD report that people use (directly or indirectly) as source, says

Australia, the Czech Republic and New Zealand report a relatively large incidence of homelessness, and this is partly explained by the fact that these countries adopt a broad definition of homelessness…..In New Zealand homelessness is defined as “living situations where people with no other options to acquire safe and secure housing: are without shelter, in temporary accommodation, sharing accommodation with a household or living in uninhabitable housing.

That’s much broader than ‘sleeping in cars, shop entrances and alleyways.” One of the researchers behind the NZ figure said, in a Herald interview in 2016

“If the homeless population were a hundred people, 70 are staying with extended family or friends in severely crowded houses, 20 are in a motel, boarding house or camping ground, and 10 are living on the street, in cars, or in other improvised dwellings.”

Homelessness is a real problem in New Zealand. Because it’s a real problem, it’s important to focus on what the problem actually is, and not to make up a different problem.

Reuters has corrected the figure but hasn’t otherwise changed the story.  The fact that reducing the figure by a factor of ten doesn’t otherwise change the story might tell you something about the story.

(update: ok, now I’ve actually read all of Toby’s post, not just the first few paragraphs, he basically says all this already)

Team Ratings for Round 15

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 87 matches played, 60 of which were correctly predicted, a success rate of 69%.
Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 15. 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 12

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 88 matches played, 49 of which were correctly predicted, a success rate of 55.7%.
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.

Team Ratings for the Final

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 134 matches played, 95 of which were correctly predicted, a success rate of 70.9%.
Here are the predictions for last week’s games.

Predictions for the Final

Here are the predictions for the Final. 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.

• David Fisher in the Herald “Garrett appeared unaware both Edgeler and Lumley had since withdrawn their comments, having found they were based on bad data from the Ministry of Justice.“
• “Why Is It So Hard to Figure Out When the Bus Is Coming?” From Citylab. At least Auckland Transport doesn’t seem to have the problem of inaccurate maps that the story focuses on.  Prediction is still hard, especially when it comes to the future.
• There was a story in the more-excitable media about alien influences on Earth species. Some species of lizards in New Guinea have toxic, bright-green blood, and they aren’t even each others closest relatives. That wasn’t the alien story, though. The alien story was about octopuses. Here’s the story the Herald republished, and here’s a more sensible one from Buzzfeed. Not only is there no evidence for it, there’s evidence against it. New Zealand has plenty of scientists who know enough evolutionary biology to say the story is crap; it wouldn’t have been hard to ask one of them.
• A tweet about toothpaste with an unusual ingredient that “increases the defenses of teeth and gums…cells are loaded with new life energy, the destroying effect of bacteria is hindered… it gently polishes the dental enamel and turns it white and shiny.” Fairly typical non-quite-therapeutic claims, but this toothpaste is from the early 20th century and the unusual ingredient is radium
• A Guardian story with a nice animated chart showing the uncertainty in global warming predictions.
• From Quartz, “Satellite images reveal which countries cheat on their economic statistics”