Posts from April 2014 (60)

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 11 2014.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of April 5 – 11 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.

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

A nice animated GIF showing what difference a small amount of simple formatting can make to a simple table. You may need to click on the image.

…”One of the problems in developing drugs is detecting serious side effects. People who need medication tend to be unwell, so it’s hard to find a reliable comparison. That’s why the roughly threefold increase in heart-attack risk among Vioxx users took so long to be detected …”

Read his column, Faulty Powers, here.

Team Ratings for Round 5

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.

Performance So Far

So far there have been 32 matches played, 14 of which were correctly predicted, a success rate of 43.8%.

Here are the predictions for last week’s games.

Predictions for Round 5

Here are the predictions for Round 5. 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. 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.

Performance So Far

So far there have been 42 matches played, 26 of which were correctly predicted, a success rate of 61.9%.

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 Fox News last week (via)

My edit based on what ended up happening

If the magnitudes don’t matter, the graph can’t be worth the pixels it’s printed on.

Statistics New Zealand has just released the meshblock-level data from last year’s Census, together with matching information for the previous two censuses (reworked to use the new meshblock boundaries).

Mashblock shows one thing that can be built with this sort of data, there are many others.

Get your meshblock files here

There’s an interesting piece in Stuff about Massey’s Illegal Drug Monitoring System. I’d like to make two points about it.

First, the headline is that synthetic cannabis use is declining. That’s good, but it’s in a survey of frequent users of illegal drugs.  If you have the contacts and willingness to buy illegal drugs, it isn’t surprising that you’d prefer real cannabis to the synthetics — there seems to be pretty universal agreement that the synthetics are less pleasant and more dangerous.  This survey won’t pick up trends in more widespread casual use, or in use by teenagers, which are probably more important.

Second, the study describes the problems caused by much more toxic new substitutes for Ecstacy and LSD. This is one of the arguments for legalisation. On the other hand, they are also finding increased abuse of prescription oxycodone. This phenomenon, much more severe in the US, weakens the legalisation argument somewhat.  Many people (including me) used to believe, based on reasonable evidence, that a substantial fraction of the adverse health impact of opioid addiction was due to the low and unpredictably-varying purity of street drugs, and that pure, standardised drugs would reduce overdoses. As Keith Humphreys describes, this turns out not to be the case.

Just a quick pointer to a nice opinion piece by the Financial Times’ “Undercover Economist” and star of BBC Radio 4’s excellent “More or Less” podcast, Tim Harford. Tim very nicely argues that in the hype over big data, stories of the failures of simplistic, correlation driven approaches rarely get airtime, and hence we get a misleading impression about the efficacy of these techniques.