Stats Chat

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 107 matches played, 63 of which were correctly predicted, a success rate of 58.9%.
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.

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday June 16 2017.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 10 – 16 2017 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

The Guardian says “Dozens of recent clinical trials may contain wrong or falsified data, claims study”

A UK anaesthetist, John Carlise, has scraped 5000 clinical-trial publications, where patients are divided randomly into two groups before treatment is assigned, and looked at whether the two groups are more similar or more different than you’d expect by chance.  His motivation appears to be that having groups which are too similar can be a sign of incompetent fraud by someone who doesn’t understand basic statistics. However, the statistical hypothesis he’s testing isn’t actually about fraud, or even about incompetent fraud.

As the research paper notes, some of the anomalous results can be explained by simple writing errors: saying “standard deviation” when you mean “standard error” — and this would, if anything, be evidence against fraud.  Even in the cases where that specific writing error isn’t plausible, looking at the paper can show data fabrication to be an unlikely explanation.  For example, in one of the papers singled out as having a big difference not explainable by the standard deviation/standard error confusion, the difference is in one blood chemistry measurement (tPA) that doesn’t play any real role in the conclusions. The data are not consistent with random error, but they also aren’t consistent with deliberate fraud.  They are more consistent with someone typing 3.2 when they meant 4.2. This would still be a problem with the paper, both because some relatively unimportant data are wrong and because it says bad things about your workflow if you are still typing Table 1 by hand in the 21st century, but it’s not of the same scale as data fabrication.

You’d think the Guardian might be more sympathetic to typos as an explanation of error.

Team Ratings for Round 16 Game, Hurricanes vs Chiefs

The basic method is described on my Department home page.

This week is pretty crazy, just one game from round 16 when round 15 has not been completed and won’t be for a month.

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 120 matches played, 91 of which were correctly predicted, a success rate of 75.8%.
Here are the predictions for last week’s games.

Predictions for Round 16, Hurricanes vs. Chiefs

Here are the predictions for the Round 16 game this week. 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 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 99 matches played, 58 of which were correctly predicted, a success rate of 58.6%.
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.

• Possibly a record false positive rate:  “a substantial number of takedown requests submitted to Google are for URLs that have never been in our search index, and therefore could never have appeared in our search results… Nor is this problem limited to one submitter: in total, 99.95% of all URLs processed from our Trusted Copyright Removal Program in January 2017 were not in our index” (Google submission to Register of Copyrights(PDF), via Techdirt)

• Problem with rental costs in Canada’s historical CPI “the clerks who recorded the data were under an instruction that, since the CPI was to represent prices paid by better off working class families, to edit out any rental figures what were above a designated threshold. By the end of the 1950s they were throwing out more than half of the reported rents.” (Worthwhile Canadian Initiative). Data doesn’t just happen: it’s choices by people.

• Graphic design: a detailed examination of  changes over the past year in Apple Maps and Google Maps

• I’ve mentioned the University of Washington course “Calling Bullshit on Big Data” before. Now the New Yorker has a story about it.

• What different sorts of things can go wrong with a statistical prediction rule? A taxonomy, from Ed Felten.

• Explore NZ mortality rates divided up by ethnicity, income, and age

• “What we learned from three years of interviews with data journalists, web developers and interactive editors at leading digital newsrooms” Storybench, via Alberto Cairo

• A couple of examples from the fine UK election tradition of disinformation graphics: Scotland, London

• XKCD takes on some favorite StatsChat topics: genetic ancestry testing, maps of US state ‘most popular whatever’

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday June 9 2017.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 3 – 9 2017 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

Q: Did you see `young blood’ cuts cancer and Alzheimer’s risk?

A: That’s the headline, yes.

Q: This is the Silicon Valley startup that’s transfusing young people’s blood into older people?

A: Well, Monterey rather than Silicon Valley, but yes.

Q: Isn’t it a pity we used up all the vampire jokes on Theranos?

A: I’m sure they aren’t really dead, just sleeping. (more…)

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 111 matches played, 85 of which were correctly predicted, a success rate of 76.6%.
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 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 92 matches played, 52 of which were correctly predicted, a success rate of 56.5%.
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.