Posts from May 2016 (41)

May 9, 2016

Stat of the Week Competition: May 7 – 13 2016

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 May 13 2016.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of May 7 – 13 2016 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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Stat of the Week Competition Discussion: May 7 – 13 2016

If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

May 7, 2016

Open data: baby names

The Herald has a headline “Emma and Noah continue to be tops for baby names”, with this link from the web front page

baby

In fact, Noah was number 11 as a baby boy’s name, and Emma didn’t make the top hundred names for baby girls in New Zealand.  The top names in NZ, as in this Stuff story from the first week of January, were Oliver and Olivia. That story also had tables and graphs from the Dept of Internal Affairs data.

The new Herald story is about the USA, where they take longer to accumulate and release the baby-name data, but where they have the indefatigable Laura Wattenberg to make sure it gets publicised.

In fact, it’s kind of surprising how much difference there is between the US and NZ lists. Enough to make it worth pointing out in the story.  UK data won’t be out for another few months. Based on last year, it’s a bit more similar to NZ. Maybe we’ll get another story then.

 

May 6, 2016

Reach out and touch someone

Q: Did you see in the Herald that texting doesn’t help relationships?

A: That’s what they said, yes.

Q: And is it what they found?

A: Hard to tell. There aren’t any real descriptions of the results

Q: What did they do?

A: Well, a couple of years ago, the researcher had a theory that “sending just one affectionate text message a day to your partner could significantly improve your relationship.”

Q: So the research changed her mind?

A: Sounds like.

Q: That’s pretty impressive, isn’t it?

A: Yes, though it doesn’t necessary mean it should change our mind.

Q: It sounds like a good study, though. Enrol some people and regularly remind half of them to send affectionate text messages.

A: Not what they did

Q: They enrolled mice?

A: I don’t think there are good animal models for assessing affectionate text messages. Selfies, maybe.

Q: Ok, so that publicity item about the research is headlined “Could a text a day keep divorce away?”

A: Yes.

Q: Did they people about their text-messaging behaviour and then wait to see who got divorced?

A: It doesn’t look like it.

Q: What did they do?

A: It’s not really clear: there are no details in the Herald story or in the Daily Mail story they took it from.  But they were recruiting people for an online survey back in 2014.

Q: A bogus poll?

A: Well, if you want to put it that way, yes. It’s not as bogus when you’re trying to find out if two things are related rather than how common one thing is.

Q: <dubiously> Ok . And then what?

A: It sounds like they interviewed some of the people, and maybe asked them about the quality of their relationships. And that people who didn’t see their partners or who didn’t get affection in person weren’t as happy even if they got a lot of texts.

Q: Isn’t that what you’d expect anyway? I mean, even if the texts made a huge difference, you’d still wish that you had more time together or that s/he didn’t stop being affectionate when they got off the phone.

A: Pretty much. The research might have considered that, but we can’t tell from the news story. There doesn’t even seem to be an updated press release, let alone any sort of publication.

Q: So people shouldn’t read this story and suddenly stop any social media contact with their sweetheart?

A: No. That was last week’s story.

 

May 4, 2016

Should you have bet on Leicester City?

As you know, Leicester City won the English Premier League this week. At the start of the season, you could get 5000:1 odds on this happening. Twelve people did.

Now, most weeks someone wins NZ Lotto first division, which pays more than 5000:1 for a winning ticket, and where we know the odds are actually unfavourable to the punter. The 5000:1 odds on their own aren’t enough to conclude the bookies had it wrong.  Lotto is different because we have good reasons to know that the probabilities are very small, based on how the numbers are drawn. With soccer, we’re relying on much weaker evidence.

Here’s Tim Gowers explaining why 5000:1 should have been obviously too extreme

The argument that we know how things work from following the game for years or even decades is convincing if all you want to prove is that it is very unlikely that a team like Leicester will win. But here we want to prove that the odds are not just low, but one-in-five-thousand low.

Professor Gowers does leave half the question unexamined, though

I’m ignoring here the well-known question of whether it is sensible to take unlikely bets just because your expected gain is positive. I’m just wondering whether the expected gain was positive.

 

Briefly

  • A historical list of data visualisations, starting in 5500BCE Mesopotamia
  • Selection bias: @_OneRandomTweet retweets one random tweet every few hours, “to remind you that people don’t use Twitter like you do
  • Richard Clark: “The boundaries of New Zealand suburbs and localities is held by the New Zealand Fire Service. For years, the NZFS has refused to provide this data under any terms except a restrictive license, and it has to stop.
  • Outsourcing: Andrew Gelman is disappointed in the NZ Herald, so I don’t have to be.
  • Survivor bias:

Super 18 Predictions for Round 11

Team Ratings for Round 11

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.

Current Rating Rating at Season Start Difference
Crusaders 9.46 9.84 -0.40
Hurricanes 8.37 7.26 1.10
Chiefs 6.23 2.68 3.60
Highlanders 5.85 6.80 -0.90
Waratahs 3.77 4.88 -1.10
Brumbies 2.05 3.15 -1.10
Stormers 1.62 -0.62 2.20
Bulls 0.59 -0.74 1.30
Sharks 0.00 -1.64 1.60
Lions 0.00 -1.80 1.80
Blues -3.88 -5.51 1.60
Rebels -5.29 -6.33 1.00
Cheetahs -7.07 -9.27 2.20
Jaguares -7.24 -10.00 2.80
Reds -8.98 -9.81 0.80
Force -11.93 -8.43 -3.50
Sunwolves -16.26 -10.00 -6.30
Kings -20.55 -13.66 -6.90

 

Performance So Far

So far there have been 78 matches played, 53 of which were correctly predicted, a success rate of 67.9%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Chiefs vs. Sharks Apr 29 24 – 22 11.40 TRUE
2 Force vs. Bulls Apr 29 20 – 42 -6.70 TRUE
3 Highlanders vs. Brumbies Apr 30 23 – 10 7.10 TRUE
4 Blues vs. Rebels Apr 30 36 – 30 5.30 TRUE
5 Reds vs. Cheetahs Apr 30 30 – 17 0.60 TRUE
6 Lions vs. Hurricanes Apr 30 17 – 50 -0.50 TRUE
7 Stormers vs. Waratahs Apr 30 30 – 32 2.40 FALSE
8 Jaguares vs. Kings Apr 30 73 – 27 13.40 TRUE

 

Predictions for Round 11

Here are the predictions for Round 11. 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.

Game Date Winner Prediction
1 Crusaders vs. Reds May 06 Crusaders 22.40
2 Brumbies vs. Bulls May 06 Brumbies 5.50
3 Sunwolves vs. Force May 07 Force -0.30
4 Chiefs vs. Highlanders May 07 Chiefs 3.90
5 Waratahs vs. Cheetahs May 07 Waratahs 14.80
6 Sharks vs. Hurricanes May 07 Hurricanes -4.40
7 Kings vs. Blues May 07 Blues -12.70

 

NRL Predictions for Round 10

Team Ratings for Round 10

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.

Current Rating Rating at Season Start Difference
Cowboys 12.60 10.29 2.30
Broncos 11.43 9.81 1.60
Storm 6.13 4.41 1.70
Roosters 3.78 11.20 -7.40
Sharks 3.11 -1.06 4.20
Eels 1.45 -4.62 6.10
Bulldogs 0.71 1.50 -0.80
Sea Eagles 0.05 0.36 -0.30
Panthers -0.02 -3.06 3.00
Raiders -0.20 -0.55 0.40
Rabbitohs -1.46 -1.20 -0.30
Dragons -3.59 -0.10 -3.50
Warriors -5.57 -7.47 1.90
Titans -6.92 -8.39 1.50
Wests Tigers -7.13 -4.06 -3.10
Knights -12.68 -5.41 -7.30

 

Performance So Far

So far there have been 72 matches played, 40 of which were correctly predicted, a success rate of 55.6%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Rabbitohs vs. Wests Tigers Apr 28 22 – 30 7.90 FALSE
2 Eels vs. Bulldogs Apr 29 20 – 12 2.90 TRUE
3 Panthers vs. Raiders Apr 30 19 – 18 0.00 TRUE
4 Roosters vs. Knights Apr 30 38 – 0 16.50 TRUE
5 Sea Eagles vs. Cowboys Apr 30 28 – 34 -10.20 TRUE
6 Warriors vs. Dragons May 01 26 – 10 -0.20 FALSE
7 Titans vs. Storm May 01 0 – 38 -5.70 TRUE
8 Sharks vs. Broncos May 01 30 – 28 -6.50 FALSE

 

Predictions for Round 10

Here are the predictions for Round 10. 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.

Game Date Winner Prediction
1 Dragons vs. Raiders May 12 Raiders -0.40
2 Eels vs. Rabbitohs May 13 Eels 5.90
3 Panthers vs. Warriors May 14 Panthers 5.60
4 Storm vs. Cowboys May 14 Cowboys -6.50
5 Broncos vs. Sea Eagles May 14 Broncos 14.40
6 Knights vs. Sharks May 15 Sharks -12.80
7 Wests Tigers vs. Bulldogs May 15 Bulldogs -7.80
8 Titans vs. Roosters May 16 Roosters -7.70

 

May 3, 2016

Bright lights, big city

From NewsHub: “NZ’s most violent city spots revealed”

The approximately one square kilometre grid follows part of Queen St and includes the area around the Sky Tower and casino, as well as the eclectic entertainment strip of Karangahape Rd.

Last calendar year 550 people were the victims of assaults, sexual attacks and robberies in this area.

That’s a rate for these violent crimes more than six-and-a-half times the national average.

The other top locations included two more areas in central Auckland, and a chunk of central Wellington including Cuba St and Courtenay Place.  One thing these four (and quite possibly some of the other top locations) have in common is that a lot of people who don’t live there spend time there — and some of these people commit or suffer violent crimes.  Auckland Central West has a very high violent crime rate for its local population, but some of that is because the relevant population isn’t just the local residents, it’s workers by day and revellers by night.   The area is presumably more dangerous than the national average, but it’s not six and a half times more dangerous.

May 2, 2016

Stat of the Week Competition: April 30 – May 6 2016

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 May 6 2016.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of April 30 – May 6 2016 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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