Posts filed under General (3156)

Team Ratings for Round 3

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 8 matches played, 7 of which were correctly predicted, a success rate of 87.5%.

Here are the predictions for last week’s games.

Predictions for Round 3

Here are the predictions for Round 3. 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.

Predictive risk scores for re-offending are increasingly used in the US. An opinion piece in the New York Times argues this is bad

The basic problem is that the risk scores are not based on the defendant’s crime. They are primarily or wholly based on prior characteristics: criminal history (a legitimate criterion), but also factors unrelated to conduct. Specifics vary across states, but common factors include unemployment, marital status, age, education, finances, neighborhood, and family background, including family members’ criminal history.

• Jawbone (who make gadgets that tell you if you’re awake and walking around) have made some interesting graphics on sleep and activity in cities around the world.

• VentureBeat argues that doctors don’t actually care about your Jawbone and Fitbit data

• Alberto Cairo writes about media graphics and constructive criticism. He’s probably right.

• the Slate Money podcast has some nice discussion of data science jobs, from a range of viewpoints (starting at about 24:45 — or listen to the whole thing and learn about Buzzfeed and about the payday loan industry)

From the Sunday Star-Times, on fish oil

Grey and colleague Dr Mark Bolland studied 18 randomised controlled trials and six meta-analyses of trials on fish oil published between 2005 and 2013. Only two studies showed any benefit but most media coverage of the studies was very positive for the industry.

On the other hand, the CEO of a fish-oil-supplement company disagrees

Keeley said more than 25,000-peer reviewed scientific papers supported the benefits of omega-3. “With that extensive amount of robust study to be then challenged by a couple of meta-analyses where negative reports are correlated together dumbfounds me.”

In fact, it happens all the time that large numbers of research papers and small experiments find something is associated with health then small numbers of large randomised trials show it doesn’t really help.  If it didn’t happen, medical and public health research would be much faster, cheaper, and more effective. I’m a coauthor on at least a couple of those 25000 peer-reviewed papers, and I’ve worked with people who wrote a bunch more of them, and I’m not dumbfounded. You don’t judge weight of evidence by literally weighing the papers.

Mr Keeley takes fish oil himself, and believes he will “live to 70, or 80 or 90 and not suffer from Alzheimer’s.”  That’s actually about what you’d expect without fish oil. He’s 60 now, so his statistical life expectancy is another 23 years, and by 83, less than 10% of people have developed dementia.

I wouldn’t say there was compelling evidence that fish-oil capsules are useless, but the weight of evidence is not in favour of them doing much good.

Team Ratings for Round 23

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 160 matches played, 91 of which were correctly predicted, a success rate of 56.9%.

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

Here are the team ratings prior to Round 1, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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.

Team Ratings for Round 2

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 4 matches played, 3 of which were correctly predicted, a success rate of 75%.

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 recent weeks, three examples of claims from self-selected samples:

• The Dominion Post: “Women still want spouse to earn more”
• The New Zealand Association of Scientists survey on perceptions of the National Science Challenges
• Dr Kate Clancy’s survey of sexual harassment in academic fieldwork, from PLoS One

In all three cases, you’d expect the pattern to generalise to some extent, but not quantitatively. The dating site in question specifically boasts about the non-representativeness of its members; the NZAS survey was sent to people who’d be likely to care, and there wasn’t much time to respond; scientists who had experienced or witnessed harassment would be more likely to respond and to pass the survey along to others.

I think two of these are worth presenting and discussing, and the other one isn’t, and that’s not just because two of them agree with my political prejudices.

The key question to ask when looking at this sort of probably non-representative sample, is whether the response you see would still be interesting if no-one outside the sample shared it. That is, the surveys tell us at a minimum

• there exist 350 women in New Zealand who wouldn’t marry a man earning less than them, and are prepared to say so
• there exist 200-odd scientists in NZ who think the National Science Challenges were badly chosen or conducted, and are prepared to say so
• there exist 417 scientists who have experienced verbal sexual harassment, and 139 who have experienced unwanted physical contact from other research staff during fieldwork, and are prepared to say so.

I would argue that the first of these is completely uninteresting, but the second is contrary to the impressions being given by the government, and the third should worry scientists who participate in or organise fieldwork.

Limits of measurement edition

• “So you can either believe that Germany has no billionaires or that European statisticians aren’t very good at finding them.” Stories from Slate and Bloomberg on the difficulty of estimating wealth inequality

• “Big data really only has one unalloyed success on its track record, and it’s an old one: Google, specifically its Web search.” Another story from Slate, on Big Data and creepy experiments.

• Lionfish are a significant exotic invader in the US, but are easy to catch and taste good. Except that they often test positive for ciguatera toxin, which is no fun at all. Except that  it might all be a false positive.

• Even for the best drink-driving propaganda, such as the famous ‘Ghost Chips’ ad, the evaluation is basically in terms of public perception, because it’s too hard to evaluate actual impact on drink driving.  A nice piece from TheWireless

Team Ratings for Round 22

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 152 matches played, 85 of which were correctly predicted, a success rate of 55.9%.

Here are the predictions for last week’s games.

Predictions for Round 22

Here are the predictions for Round 22. 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.