Stats Chat

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 7 matches played, 5 of which were correctly predicted, a success rate of 71.4%.
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.

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.
Note that Cheetahs2 refers the Cheetahs team when there is a Pro14 match. The assumption is that the team playing in the Pro14 is the top team and the Currie Cup team is essentially a second team.

Performance So Far

So far there have been 2 matches played, 1 of which were correctly predicted, a success rate of 50%.
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.

This year’s census already been the subject of some news reports, some of which have quoted me.  I’ve now been appointed to an external data quality panel advising StatsNZ,  and I will be much more limited in what I can say in the future here or to journalists.  That’s partly just ordinary confidentiality to make the panel discussions work effectively, and partly because we’ll be seeing unreleased data whose disclosure is prohibited by the Statistics Act.

Team Ratings for Round 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.

Note that Cheetahs2 refers to the Cheetahs team when there is a Pro14 match. The assumption is that the team playing in the Pro14 is the top team and the Currie Cup team is essentially a second team.

Predictions for Round 1

Here are the predictions for Round 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.

• From the Guardian: Mapping the world’s cities where you can live comfortably without heating or air conditioning reveals how few boast such ideal climates.  Among the cities that apparently don’t need heating or AC are Auckland and Melbourne.  Not entirely convincing.
• From the Herald:  Scientists accidentally discover pill which could stop weight gain. What they actually discovered was a way to genetically engineer mice not to gain weight.  There’s a drug used to treat glaucoma that affects the same biochemical mechanism that the genetic engineering did — but it’s used as eyedrops to treat glaucoma, so that’s not great evidence it would be safe and effective as a pill.
• Peter Ellis has been analysing petrol-price data after the Auckland tax was imposed: “after the spike caused by the tax, fuel prices in Auckland and in the rest of the country are converging somewhat (although much less than the full cost of the tax), and plausibly this is because of companies’ price adjustments down in Auckland and up elsewhere to spread the cost of the tax over a broader base.”
• I’ve written a program to produce a map of Wellington-area buses showing how many are late.  It’s not quite real-time; it shows roughly the past hour. The map is here (you can click on the markers); the (more-technical) blog post explaining how it works is here.

Team Ratings for Round 23

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 168 matches played, 102 of which were correctly predicted, a success rate of 60.7%.
Here are the predictions for last week’s games.

Predictions for Round 23

Here are the predictions for Round 23. 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 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 Round 1

Here are the predictions for Round 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.

• Navigating word relationships from Wikipedia, spaceship-style:
• But just because social problems aren’t surprising doesn’t mean they aren’t worth mapping. Just because maps are similar doesn’t mean they’re actually the same. From Pro Publica, on maps of inequality in Chicago and similar topics
• Privacy issues with deep neural networks: they remember a lot more than they are asked to. 
• The Royal Statistical Society announces its Statistical Excellence in Journalism awards. Well deserved.

Q: Did you see that smartphones make you go blind?

A: Doesn’t it depend on what you do while you’re using them?

Q: No, the headline says Blue light from phone screens accelerates blindness, study finds.  And it goes on Light from digital devices triggers creation of toxic molecule in the retina that can cause macular degeneration

A: Yeah nah

Q: They didn’t study phone screens?

A: No

Q: Macular degeneration?

A: No

Q: Retinas?

A: Not as such, no.

Q: Ok, so was it mice? It’s always mice, isn’t it.

A: No, this was cells grown in a lab from standard cell lines then genetically engineered to produce the chemicals the eye uses to see blue light. Some of them were originally derived from mouse cells, and some were originally derived human cells — like the famous HeLa cell line.

Q:

A: You were going to mention that Thor movie, weren’t you?

Q: No, I’ve read The Immortal Life of Henrietta Lacks. Everyone should. But we nearly digress. If they didn’t use digital screens, what did they use? Sharks with lasers on their heads?

A: Close. No sharks. LED lasers.

Q: So why does this show phones make you go blind?

A: That isn’t what they were trying to do. They already believed blue light caused macular degeneration, and they were trying to find out how that works, on a molecular level. It’s clearer from their press release, though that still talks a lot about phones — the newspaper didn’t make this one up.

Q: Is it in the original research paper?

A: No, that’s written in High Biochemist. It’s got subheadings likeBLE-retinal induced PIP2 distortion is independent of GPCR-G protein activation

Q: How do phones even compare as a source of blue light, compared to other sources? Police car lights? University-themed webpages? The sky?

A: Even though your eyes squinch up in bright sunlight, the sun and the sky are going to be the big contributor

Q: Especially if your phone and computer switch to a tasteful sepia colour scheme at night, like they tend to nowadays.

A: So, maybe sunglasses.

• From the NY Times Upshot blog: a randomised trial finds little or no effect of providing a workplace wellness program — but within the trial, the people who ended up using the program were healthier. It would have looked effective without randomisation
• The US National Academy of Science joins the groups saying it’s a bad idea to add a last-minute citizenship question to the US census.
• “Raising the Bar” is a set of 20 talks in bar by Auckland academics, held on Tuesday 28th August. Some of them are sold out already, but the remaining ones include Andrew Chen on  privacy implications of modern  surveillance systems and Cather Simpson on useful and fun things she does with lasers.
• This graph appeared at vox.com,
  As Kieran Healy tweeted “that 1-year, ~15lb-per-person jump in vegetable fat consumption c. 2000 is weird, and a candidate for the rule of thumb that sudden jumps in a time series are often due to changes in measurement criteria”.  And so it was.  Official statistics agencies try not to change their definitions without a good reason, and put this sort of thing in footnotes. Which you need to check.