April 17, 2014

This is not a map

Changing-face

 

This is not a map. The Asian population of the US is not confined to Maine and northern Washington, and residents of the Dakotas are not primarily Black and Hispanic. It’s a stacked line plot, which has been cut out to fit the map outline, just like you might do in kindergarten. (via Flowing Data)

Here’s the real thing, from Pew Research.

map

April 16, 2014

NRL Predictions for Round 7

Team Ratings for Round 7

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.

Current Rating Rating at Season Start Difference
Roosters 7.55 12.35 -4.80
Rabbitohs 6.40 5.82 0.60
Bulldogs 6.24 2.46 3.80
Sea Eagles 5.95 9.10 -3.10
Cowboys 2.89 6.01 -3.10
Knights 2.86 5.23 -2.40
Storm 2.24 7.64 -5.40
Titans 0.26 1.45 -1.20
Broncos -1.83 -4.69 2.90
Sharks -2.75 2.32 -5.10
Panthers -2.92 -2.48 -0.40
Wests Tigers -4.13 -11.26 7.10
Warriors -4.40 -0.72 -3.70
Raiders -5.45 -8.99 3.50
Dragons -5.47 -7.57 2.10
Eels -9.20 -18.45 9.30

 

Performance So Far

So far there have been 48 matches played, 24 of which were correctly predicted, a success rate of 50%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Panthers vs. Rabbitohs Apr 11 2 – 18 -2.30 TRUE
2 Titans vs. Broncos Apr 11 12 – 8 7.30 TRUE
3 Raiders vs. Knights Apr 12 12 – 26 -1.50 TRUE
4 Eels vs. Roosters Apr 12 14 – 12 -15.40 FALSE
5 Wests Tigers vs. Cowboys Apr 12 16 – 4 -5.70 FALSE
6 Warriors vs. Bulldogs Apr 13 20 – 21 -7.40 TRUE
7 Sea Eagles vs. Sharks Apr 13 24 – 4 11.60 TRUE
8 Storm vs. Dragons Apr 14 28 – 24 14.10 TRUE

 

Predictions for Round 7

Here are the predictions for Round 7. 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 Rabbitohs vs. Bulldogs Apr 18 Rabbitohs 4.70
2 Knights vs. Broncos Apr 18 Knights 9.20
3 Sea Eagles vs. Cowboys Apr 18 Sea Eagles 7.60
4 Dragons vs. Warriors Apr 19 Dragons 3.40
5 Sharks vs. Roosters Apr 19 Roosters -5.80
6 Raiders vs. Storm Apr 20 Storm -3.20
7 Eels vs. Wests Tigers Apr 21 Wests Tigers -0.60
8 Panthers vs. Titans Apr 21 Panthers 1.30

 

Super 15 Predictions for Round 10

Team Ratings for Round 10

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.

Current Rating Rating at Season Start Difference
Sharks 7.52 4.57 3.00
Crusaders 7.20 8.80 -1.60
Chiefs 4.10 4.38 -0.30
Brumbies 4.06 4.12 -0.10
Waratahs 3.18 1.67 1.50
Bulls 2.88 4.87 -2.00
Stormers 0.66 4.38 -3.70
Hurricanes 0.51 -1.44 1.90
Reds -0.84 0.58 -1.40
Blues -1.33 -1.92 0.60
Force -2.44 -5.37 2.90
Highlanders -3.83 -4.48 0.70
Cheetahs -4.29 0.12 -4.40
Rebels -5.18 -6.36 1.20
Lions -5.22 -6.93 1.70

 

Performance So Far

So far there have been 55 matches played, 34 of which were correctly predicted, a success rate of 61.8%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Highlanders vs. Bulls Apr 11 27 – 20 -4.10 FALSE
2 Reds vs. Brumbies Apr 11 20 – 23 -2.30 TRUE
3 Chiefs vs. Rebels Apr 12 22 – 16 14.40 TRUE
4 Force vs. Waratahs Apr 12 28 – 16 -5.20 FALSE
5 Cheetahs vs. Crusaders Apr 12 31 – 52 -5.60 TRUE
6 Lions vs. Sharks Apr 12 12 – 25 -9.80 TRUE

 

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 Hurricanes vs. Blues Apr 18 Hurricanes 4.30
2 Rebels vs. Force Apr 18 Force -0.20
3 Chiefs vs. Crusaders Apr 19 Crusaders -0.60
4 Waratahs vs. Bulls Apr 19 Waratahs 4.30
5 Sharks vs. Cheetahs Apr 19 Sharks 14.30
6 Stormers vs. Lions Apr 19 Stormers 8.40

 

Ways not to use the Global Drug Use Survey

We learned previously from Stuff and the Global Drug Use Survey that 22% of New Zealanders have used synthetic cannabis. Today

Results from this year’s Global Drug Survey, conducted in partnership with Fairfax Media, found almost 4 per cent of synthetic cannabis users sought emergency medical treatment. More than a quarter of those were admitted to hospital.

It simply cannot be true that 4% of 22% of the country has sought emergency treatment after using synthetic cannabis. Even restricting to adults, that’s 30,000 people, with more 7,500 admitted to hospital. In the most recent year for which I can find data (2010-11, when the drugs were more widely available than now) there were 672,000 publicly funded hospital admissions for all causes, and of those, only 896 were for cause categories X41 & X42, which would include all synthetic cannabis cases plus many others.

[update: fixed typo in numbers]

April 14, 2014

What do we learn from the Global Drug Use Survey?

drug

 

That’s the online summary at Stuff.  When you point at one of the bubbles it jumps out at you and tells you what drug it is. The bubbles make it relatively hard to compare non-adjacent numbers, especially as you can only see the name of one at a time. It’s not even that easy to compare adjacent bubbles, eg, the two at the lower right, which differ by more than two percentage points.

More importantly, this is the least useful data from the survey.  Because it’s a voluntary, self-selected online sample, we’d expect the crude proportions to be biased, probably with more drug use in the sample than the population. To the extent that we can tell, this seems to have happened: the proportion of past-year smokers is 33.5% compared to the Census estimate of 15% active smokers.  It’s logically possible for both of these to be correct, but I don’t really believe it.  The reports of cannabis use are much higher than the (admittedly out of date) NZ Alcohol and Drug Use Survey.  For this sort of data, the forthcoming drug-use section of the NZ Health Survey is likely to be more representative.

Where the Global Drug Use Survey will be valuable is in detail about things like side-effects, attempts to quit, strategies people use for harm reduction. That sort of information isn’t captured by the NZ Health Survey, and presumably it is still being processed and analysed.  Some of the relative information might be useful, too: for example, synthetic cannabis is much less popular than the real thing, with past-year use nearly five times lower.

Peak car?

From the Herald, quoting the chief executive of Z Energy:

“People are doing online shopping and Skyping granny rather than making the fortnightly visit.”

A 1 per cent improvement in broadband connectivity is estimated to cause a drop of 200 million litres a year in national fuel demand, more than the impact of GDP growth, population, fleet turnover, vehicle efficiency and the petrol price.

The first question here is on units. For broadband, it’s fuel demand per 1% of connections, but what are the units for the others?

There’s a bit more detail in this set of slides, including this picture, where the orange bar shows the estimated effect of an increase in the factor and the yellow bar shows the estimated effect of the same decrease.

z-trends
So if we believe these numbers, a 1% point increase in broadband has slightly larger impact than a 1% increase in GDP and about twice the impact of a 1% increase in population.

For this model to be useful in prediction, which is what Z Energy presumably made it for, there’s no need that these statistical associations are causal. It’s only necessary that they persist at roughly the same strength through the period of the forecast.  The associations can’t really be true under serious extrapolation. For example, reducing broadband coverage from the current roughly 80% of households to zero would probably not cause transport fuel use to rise by 16 billion litres — ie, more than triple. Similarly, it can’t really be true that the impact nominal petrol prices is independent of inflation or income trends. For prediction this doesn’t necessarily matter, but for interpreting causes it does.

The actual prediction impact of broadband depends on how much it will increase. It turns out that the model says the reduction due to broadband plus the reduction due to increasing petrol prices approximately cancels out the increase due to increasing GDP. So, in fact, in the Z Energy model, broadband is less important than GDP growth. The model ends up predicting that per-capita travel will be roughly constant,  that total travel will increase with population, and that fuel efficiency will increase.

So, is the broadband association causal? It easily could be. There’s evidence from other countries of a reduction in driving that can’t entirely be attributed to the Great Recession. This is especially true among young people, with more socialising electronically. Telecommuting probably plays a role, too. I’m not convinced that online shopping has had a big impact on car trips in NZ, but it could have.  On the other hand, there huge uncertainty in the size of the effect — not just statistical uncertainty based on the data, but uncertainty about what’s fundamentally going on.

Finally, one depressing, but probably accurate, feature of the predictions is that they assume we still won’t be doing anything about climate change by 2018.

Stat of the Week Winner: April 5 – 11 2014

Thanks to James Green for nominating this fascinating statistic (if true):

“A 1 per cent improvement in broadband connectivity is estimated to cause a drop of 200 million litres a year in national fuel demand”

The NZ Herald quoted this (without attribution) but Thomas Lumley tracked down the source of the statistic to a report by Z Energy. The report contains no further details on the statistic.

James wrote:

“Would be fascinating if true, but without them revealing an actual source, seems difficult and barely credible to firmly link these two.”

Congratulations James for being our Stat of the Week Winner!

Stat of the Week Competition: April 12 – 18 2014

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 April 18 2014.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of April 12 – 18 2014 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…)

April 13, 2014

Housing affordability map

Saeid Adli and Alex Raichev have made interactive maps of Auckland and Wellington that try to combine the cost of housing (rent) and commuting, and present it as a fraction of income.  You can select income, house size, mode of transport, how often you commute, etc.

They also provide an explanation of how they do the calculations, and all the code and data.

Briefly