Posts filed under General (443)

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

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.

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

April 10, 2014

Frittering away

Q: Did you see that “some generation Y foodies are spending up to $600 a week on gourmet produce such as seafood, cheeses, olives and cured hams.”

A: In the Herald? Yes.

Q: Is it true?

A: Slightly.

Q: Who are these people?

A: Well, for a start, they’re Australians

Q: Oh. How many is “some”

A: At least one.

Q: No, seriously, how many?

A: 1% of a the 18-34 subset of a sample of ‘over’ 1000. Here’s the full report

Q: How many is that?

A: Maybe three in the sample?

Q: Three people or three households?

A: A good question. They don’t say, though the average weekly food expenditure in their sample looks reasonably close to the national household average that they cite.

Q: How were the people sampled?

A: They don’t say.

Q: How many were Generation Y?

A: They don’t say

Q: How did they even define ‘gourmet food’? Or don’t they say that either?

A: Sadly, no.

Q: This report doesn’t seem to follow the code of practice you blogged about recently, does it?

A: That was just for political polls, and anyway this report is Australian.

Q: Is there anything else you want to complain about in the report?

A: If  you call it an “Inaugural” report you really can’t use it to conclude “Australians are becoming a more food savvy nation”.

 

April 9, 2014

Briefly

Pie chart edition

piechartpie_custom-04484aacfec019c8444fa1b42dbdb33f71b80ed9-s40-c85

April 8, 2014

Busable Auckland

Bus commuter services can be very useful in reducing traffic and parking congestion in the city center, but reducing the average number of cars per household requires buses that are available all the time. I used the Auckland Transport bus schedule data and the new StatsNZ meshblock data and boundary files

Here’s a map of Auckland showing how many hours per day (on average) there are at least six bus trips per hour stopping within 500m of each meshblock (actually, within 500m of the ‘label point’ for the meshblock).

On a single road, six trips per hour is one trip in each direction every twenty minutes. The dark purple area has this level of service at least 16 hours a day on average. (Click for the honking great PDF version.)

bus6png

For twelve trips per hour (eg, one every twenty minutes on two different routes) the area shrinks a lot

bus12png

The reason for using meshblocks in the map is that we can merge the bus files with the census files. For example, for Auckland as a whole, 50% of the population is in the grey busless emptiness, 17% in the 8-16 hour tolerable zone, and 12% in the pretty reasonable 16+ hour zone.   People of Maori descent are more likely to be unbused (60%) and less likely to be well bused (8%), as are people over 65 (60% in the lowest category, 9% in the highest).

Recent (<10 years) migrants like transit: 18% of us are in the good bus category and only 40% in the busless category.

On talking to people