Posts from September 2015 (45)

This (via @albertocairo) is from the Guardian, two years ago.

At first it looks like a pie chart, but it isn’t. It’s a set of bar charts warped into a circle, so that the ratio of blue and red areas in a wedge is the square of the ratio of the numbers. Also, the circle format means the longest wedge in each pair must be the same length: 8.6% unemployment rate is the same as 4.6% military expenditure, 104% market capitalisation, and 46 Olympic gold medals.

Many of these are proportions or per-capita figures, but not all. Carbon emissions are national totals, making China look worse. Film industry revenues and exports are totals; they are also gross revenues — because the whole visual metaphor falls apart completely for numbers that can be negative. That’s why the current-year budget surplus/deficit isn’t treated like the other numbers.

There are also some unusual definitions. “Social media”, the bar where China is furthest behind, is defined just by the proportion who use Facebook, which obviously underestimates the social-media activity of the US (and also, perhaps, of China).

The post has some discussion of the difficulties — for example, the measurement and even the definition of unemployment in the two counties — and is much better than the graph.

Here’s a different take on the same countries, in the same format, from the World Economic Forum

They have similar problems with total vs proportion/mean variables. They solve the y-axis problem by working with international ranks, which at least gives a common scale. However, having 1 as the largest rank and some unspecified large number as the smallest rank does make the relationship between area and number fairly weird.  It also means that the actual numbers for each wedge aren’t fractions of a total in any sensible way.

If the main point is to be an eye-catching hook for the story, the Guardian graph is more successul

I decided updated ratings and predictions would be a good idea at this time. I can then post new predictions before the next games after September 27, which are on September 29.

Team Ratings at 25 September

The basic method is described on my Department home page.

Here are the team ratings prior to 25 September along with the ratings at the start of the Rugby World Cup.

Performance So Far

So far there have been 12 matches played, 10 of which were correctly predicted, a success rate of 83.3%.
Here are the predictions for previous games.

Predictions for 25 September to 27 September

The prediction is my estimated expected points difference with a positive margin being a win to the first-named team, and a negative margin a win to the second-named team.

• Ways to communicate uncertainty in economic forecasts, from Significance magazine (via Diego Kuonen)

• From National Geographic, Taking Data Visualization From Eye Candy to Efficiency (via @albertocairo)

• A visualisation of the history of the All Blacks, from Harkanwal Singh in a story by Dylan Cleaver at the Herald

• Properly conducted web-based surveys aren’t necessarily that bad (from Pew Research) “Of 406 separate estimates taken from nine waves of the American Trends Panel, just nine of them differed by 5 percentage points or more. Perhaps not surprisingly, all nine are related to internet or digital technology use. A Web-only survey estimated that 82% of the public uses the internet on a daily basis, while the full sample (including non-internet users) finds 69% go online daily.”

• Aardwolf Research is doing a flag-preference poll (mentioned in Stuff).  On the good side, they have sensible ways of looking at lots of possible flags. On the bad side, we don’t have lots of possible flags any more. On the good side they collect demographic data that could be used to get fairly representative weighted results from their self-selected internet sample. On the bad side, their results from the first wave don’t seem to use the demographic data at all.

Usually, when there’s a very expensive medication in the news it’s because some company has just invented it and is trying to make as much money as possible before there’s competition– either from other similar drugs or from generic versions.   This is (presumably) the issue that Hillary Clinton is planning to address. The manufacturer is charging all the market will bear, but it’s not precisely a case of the uncaring free market. The drugs can only be that expensive because the government deliberately gives one company a monopoly, which we do as a strategy by society to bribe companies to invent drugs that work.  Like lots of people, I think the details could be improved but the basic idea is sensible.

Yesterday’s story (Stuff, Herald) is somewhat different. An existing, off-patent, treatment is having its price jacked up enormously. It’s about 50 times what it was recently, and 750 times what it was in 2010 when the drug was owned by a huge multinational, GSK. Derek Lowe (a drug company chemist) has some good posts about this. I’m mostly summarising.

There have been a few of these cases over the past few years, with different mechanisms.  The first is a well-meaning but poorly-designed idea of the FDA to collect evidence about drugs that were already in use when effectiveness testing was brought in. For some of these drugs, knowing whether (or how well) they actually work would be valuable. In return for doing the clinical trials to modern standards, a company can get a period of ‘marketing exclusivity’ on an old off-patent drug. Unfortunately, a company can pick up a drug where there isn’t any real doubt about effectiveness, so the trials provide little benefit, and then raise the price through the roof.

The second approach is to pick a drug that has no alternatives but where the total market is small enough that getting through the FDA approval process even for a generic is enough of an obstacle to keep out competitors.  One of the recent stories was about cycloserine, a last-ditch treatment for drug-resistant tuberculosis. There are still very few cases of this in the US — about 90 per year — so even a twenty-fold price increase doesn’t open up much of a market opportunity. The regulatory problem here is the impact of high standards for demonstrating manufacturing safety. Ordinarily that’s something you want, but for very rare diseases it provides a barrier to competition.

The third mechanism really looks like a regulatory loophole, and that’s what just happened with Daraprim for treating toxoplasmosis. The active ingredient of Daraprim, pyrimethamine, is off patent. There isn’t any FDA marketing exclusivity, either. But you can’t sell it as a drug unless you show that your formulation of pyrimethamine delivers a sufficiently-similar dose with sufficiently-similar timing to the formulation that was originally approved.

Toxoplasmosis isn’t as rare as drug-resistant TB, and historically the idea was that  an attempt to charge extortionate prices couldn’t work because someone would make a generic competitor. The trick is that you would need a supply of Daraprim to show that your formulation is close enough. You can’t do that if they won’t sell it to you.

As a concept, this goes back to a lawsuit over thalidomide (which now has a couple of genuine medical uses). One US company, Celgene, had the patent. Another company, Lannett, wanted to buy some of their drug to do bioequivalence studies, and claimed Celgene was refusing only to block competition. Celgene claimed they were just worried about Lannett’s safety procedures — which, in the case of thalidomide, could be fair enough.  They settled the case and it doesn’t really matter who was right; whether Lannett was paranoid or Celgene was cheating the system, the idea was out.

Team Ratings for Week 2

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 Rugby World Cup.

Performance So Far

So far there have been 8 matches played, 6 of which were correctly predicted, a success rate of 75%.
Here are the predictions for last week’s games.

Predictions for Week 2

Here are the predictions for Week 2. The prediction is my estimated expected points difference with a positive margin being a win to the first-named team, and a negative margin a win to the second-named team.

Team Ratings for the Preliminary Finals

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 198 matches played, 117 of which were correctly predicted, a success rate of 59.1%.
Here are the predictions for last week’s games.

Predictions for the Preliminary Finals

Here are the predictions for the Preliminary 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.

Team Ratings for Round 7

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 46 matches played, 32 of which were correctly predicted, a success rate of 69.6%.
Here are the predictions for last week’s games.

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.

Team Ratings for Round 8

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 28 matches played, 20 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for Round 8

Here are the predictions for Round 8. 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.

From the Herald

Auckland renters can expect to pay a minimum $400 a week – regardless of property type or size, according to Trade Me Property’s monthly report on median rents across New Zealand.

From a quick TradeMe search for Auckland rentals, with an upper limit of $350 a week: 525 listings.

What they mean is that the median is at least $400/week in every category of property type or size, not the minimum.  That’s a bit clearer from the press release, which has data tables that the Herald didn’t print, but even that starts

A property renter in Auckland can now expect to pay $400 per week regardless of property size or type

No. No, it isn’t.

According to my searches, maybe half a dozen people asked a version of that question before the Herald headline turned up. If you count the retweets and favourites you might possibly get to twenty.

As a failure to actually search, this might beat the Netsafe CTO saying, a couple of years ago

You type ‘kiwi chicks’ into Google and the images that come back won’t be small feathered birds.”