Posts from October 2013 (67)

An improved version of study that Stuff and StatsChat reported on more than a year ago has now appeared in print. The study found that people who have non-standard beliefs about the moon landings or Princess Diana’s death are also likely to have non-standard beliefs about climate change or health effects of tobacco. It improves on the previous research by using a reasonably representative online survey rather than a sample of visitors to climate debate blogs.

Mother Jones magazine in the US summarised some of the results in this graph of correlations

That’s a horrible graph partly because, contrary to what the footnote says, correlations are not in fact restricted to be between 0 and 1, but between -1 and 1: and in fact the three correlations shown were negative in the research and have been turned around for more convenient display.

The title is misleading: only one of the six `conspiracist ideation’ questions was about 9/11, and it wasn’t a yes/no question, and it wasn’t really about it being an inside job (ie, performed by the government), but about the government allowing it to happen. In the same way, the other three variables aren’t simple yes/no questions, but scores based multiple questions, each on a 5-point scale.

A more-technical point is that correlations, while appropriate in the paper as part of their statistical model, aren’t really a good way to describe the strength of association.  It’s easier to understand the square of the correlation, which gives the proportion of variability in one variable explained by the other.  That is, the conspiracy-theory score explains about 25% of the variation in the vaccine score,  just over 1% of the variation in the GM Foods score, and just under 1% of the variation in the climate change score.

(via @zentree)

If the PubMed research database is still surviving the US government shutdown, you can read a paper published 63 years ago today on lung cancer

In England and Wales the phenomenal increase in the
number of deaths attributed to cancer of the lung provides
one of the most striking changes in the pattern of
mortality recorded by the Registrar-General. For example,
in the quarter of a century between 1922 and 1947 the
annual number of deaths recorded increased from 612 to
9,287, or roughly fifteenfold. This remarkable increase is,
of course, out of all proportion to the increase of population

Some people were arguing that the increase was just due to better diagnosis of lung cancer, and even  those who believed in a real increase weren’t sure of the reason

Two main causes have from time to time been put forward:
(1) a general atmospheric pollution from the exhaust
fumes of cars, from the surface dust of tarred roads, and
from gas-works, industrial plants, and coal fires; and
(2) the smoking of tobacco.

Richard Doll and Austin Bradford Hill decided to compare histories of smoking in lung cancer patients and those in hospital for other reasons. As you know, they found that the lung cancer patients were much more likely to be heavy smokers. It’s also interesting to read what other possibilities they considered, and how they tried to rule them out.

This sort of study isn’t completely definitive, and, famously, the eminent statistician and geneticist (and heavy smoker) R. A. Fisher was never convinced. He thought that genetic factors might well be responsible. Further evidence was provided by experiments in animals (such the ‘smoking beagles‘ of Duke University) showed that smoking really could cause cancer. Also, much more recently, studies of twins and studies that actually measured genotypes showed that genetic differences weren’t a big enough contributor to lung cancer to explain the correlation.

In contrast to, say, alcohol or opium, tobacco has been a public health problem only for about a century: tobacco smoking became very widespread in men during the first world war. With a bit of effort and some luck, future generations might see it as an inexplicable historical anomaly, like a deadly version of canasta.

The Data Journalism handbook online

And one of the additional resources on the internet: Cathy O’Neil’s On Being a Data Skeptic.

Team Ratings for Round 8

Here are the team ratings prior to Round 8, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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 54 matches played, 41 of which were correctly predicted, a success rate of 75.9%.

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.

Team Ratings for Round 9

Here are the team ratings prior to Round 9, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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 24 matches played, 12 of which were correctly predicted, a success rate of 50%.

Here are the predictions for last week’s games.

Predictions for Round 9

Here are the predictions for Round 9. 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 the Grand Final

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 200 matches played, 121 of which were correctly predicted, a success rate of 60.5%.

Here are the predictions for last week’s games.

Predictions for the Grand Final

Here are the predictions for the Grand Final. 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.

Bob Jones, in the Herald

But although the offenders are male, 99.999 per cent of men are not rapists and feel just as outraged as women do about it.

He’s obviously just pulled that number out of his head (or somewhere else round and inappropriate), since it would imply only about 20 male rapists in New Zealand. About 20 times that number were convicted and sent to prison just last year for sexual assault or aggravated sexual assault.

A lot of men have a hard time believing that rape is as common as it is — either because they can’t imagine doing it, or because they do it and don’t think it’s rape. But there are good-quality high response-rate surveys showing that lots of women have been raped, and if only a tiny minority of men are rapists, they have to be very busy.

Bob Jones is off by at least three, and quite likely more than four orders of magnitude. That must be close to a record.

(update)