Stats Chat

• Visualizing the Twitter networks of NZ MPs: on the Herald data blog, a post by Chris McDowall, and additional graphics by Jayne Ihaka.  
  Now we just need a way to tell which accounts are actually used by MPs and which ones are twitterwallahs.

• There was a big discrepancy among bookies on the odds for the Greek referendum. Paddy Power estimates an 80% chance of ‘yes’ and has paid out winnings early. Betfair is almost certain of “No”.  The wisdom of crowds has definite limitations, especially in situations where no-one really has a clue.

•  Kate Hannah, on the Te Punaha Matatini blog, writing about women and Royal Society of New Zealand prizes (which in their case they have not got)

• Sense about Science have a new guide to screening tests. I’ll repeat my testing soundbite: “Screening is the opposite of treatment: you go in healthy and come out with a disease”.

• Measuring happiness: a discussion at the New York Times and an independent (I think) skeptical post by John Quiggin arguing for measures of unhappiness.

Team Ratings for Round 17

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 118 matches played, 67 of which were correctly predicted, a success rate of 56.8%.

Here are the predictions for last week’s games.

Predictions for Round 17

Here are the predictions for Round 17. 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 124 matches played, 81 of which were correctly predicted, a success rate of 65.3%.

Here are the predictions for last week’s games.

Prediction for the Final

Here is the prediction 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.

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 July 3 2015.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 27 – July 3 2015 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.

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On Twitter, Evelyn Lamb pointed me to the poem “A contribution to Statistics”, by Wisława Szymborska (who won the 1996 Nobel Prize for Literature). It begins

Out of every hundred people

those who always know better:
— fifty-two,

doubting every step
   — nearly all the rest,

glad to lend a hand
if it doesn’t take too long:
— as high as forty-nine,

Read all of it here

The same blog, “Poetry with Mathematics”, has some other statistically themed poems:

• The Beauty of the Curve Kathleen Flenniken
• Tuberculosis in Numbers M. Brett Gaffney
• After Math Mary Alexandra Agner

The last was written in honour of Florence Nightingale, who was the first female member of the Royal Statistical Society, and also an honorary member of the American Statistical Association.

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 110 matches played, 62 of which were correctly predicted, a success rate of 56.4%.

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 the Qualifying Finals: Correction

I made a mistake in entering the fixtures and had the Waratahs playing away.

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 122 matches played, 80 of which were correctly predicted, a success rate of 65.6%.

Here are the predictions for last week’s games.

Predictions for the Qualifying Finals

Here are the predictions for the Qualifying Finals. 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.

Brent Edwards on Radio NZ’s Checkpoint has done a good job of fact-checking claims about refugee numbers in New Zealand.  Amnesty NZ tweeted this summary table

If you want the original sources for the numbers, the Immigration Department Refugee Statistics page is here (and Google finds it easily).

The ‘Asylum’ numbers are in the Refugee and Protection Status Statistics Pack, the “Approved” column of the first table. The ‘Family reunification’ numbers are in the Refugee Family Support Category Statistics Pack in the ‘Residence Visas Granted’ section of the first table. The ‘Quota’ numbers are in the Refugee Quota Settlement Statistics Pack, in the right-hand margin of the first table.

Update: @DoingOurBitNZ pointed me to the appeals process, which admits about 50 more refugees per year: 53 in 2013/4; 57 in 2012/3; 63 in 2011/2; 27 in 2010/11.

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 26 2015.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 20 – 26 2015 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.

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The Herald (from the Daily Mail)

A sunshine break is the perfect way to unwind, catch up on your reading and top up that tan.

But it seems a week soaking up the rays could also offer a surprising benefit – helping a woman have a baby.

Increased exposure to sunshine could raise the odds of becoming a mother by more than a third, a study suggests.

If you read StatsChat regularly, you probably won’t be surprised to hear the study had nothing to do with either holidays or sunbathing, or fertility in the usual sense.

As the story goes on to say, it was about the weather and IVF success rates. The researchers looked for correlations between a variety of weather measurements and a variety of ways of measuring IVF success. They didn’t find evidence of correlations with the weather at the time of conception. As they said (conference abstract, since this isn’t published)

When looking for a linear correlation between IVF results and the mean monthly values for the weather, the results were inconsistent.

So, following the ‘try, try again’ strategy they looked at weather a month earlier

However, when the same analysis was repeated with the weather results of 1 month earlier, there was a clear trend towards better IVF outcome with higher temperature, less rain and more sunshine hours. 

It helps, here, to know that “a clear trend” is jargon for “unimpresssive statistical evidence, but at least in the direction we wanted”.  That’s not the only problem, though. Since these are honest researchers, you find the other big problem in the section of the abstract labelled “limitations”

Because of the retrospective design of the study, further adjusting for possible confounding factors such as age of the woman, type of infertility and indication for IVF is mandatory. 

That is, their analysis lumped together women of different ages,  types of infertility, and reasons for using IVF, even those these have a much bigger impact on success than is being claimed for the weather.

I don’t have any problem with these analyses being performed and presented to other consenting scientists who are trying to work out ways to improve IVF.  On the other hand,  I’m pretty sure the Daily Mail didn’t get these results by reading the abstract book or sitting through the conference. Someone made a deliberate decision to get publicity for this research, at this stage, in a form where all the cautionary notes would be lost.