Stats Chat

David Farrar at Kiwiblog provides some new local examples and discussion of question-wording effects in surveys, including the gender/pay issue and same sex marriage.

“With poll questions there is rarely a clearly “right” or “wrong” question. There can be a dozen different ways to ask a question. The important thing is that the poll results make it very clear the exact question that was asked, and that reporting of the results does the same.”

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The Economist has updated its Big Mac Index:

“The Economist’s Big Mac index is a fun guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of a basket of goods and services around the world.”

At market exchange rates, a burger is 9% more expensive in New Zealand than in America. In other words, the raw Big Mac index suggests that the NZD is 9% overvalued against the US dollar. Adjusting for GDP per person, the NZD is 29% overvalued.

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From the NZ Herald:

“The survey found almost 65 per cent of women believed they were paid less because of their gender. Just under 43 per cent of men agreed but 47 per cent didn’t.”

Unfortunately the Herald doesn’t tell us what the actual question was. Were people asked whether they, personally, were paid differently because of their gender, or whether women, on average, were paid less because of their gender?   In either case, my sympathies are with Women’s Affairs Minister Hekia Parata, who refused to offer her own answer to the “simplistic” poll question.

There are two statistical problems here. The first is what we mean by “because of their gender”.  After that’s settled, we have the problem of finding data to answer the question.  Inference about cause and effect from non-experimental data will always be hard because of both problems, but that’s what we’re here for.

Usually, when we say that income or health is worse because of some factor, we mean that if you could experimentally change the factor you would change health or income. We say high blood pressure causes strokes, and we mean that if you lower the blood pressure of a bunch of people, fewer of them will get strokes.  This isn’t possible for gender — not only can we not assign gender at random, we can’t even say what it would mean to do that.  Would a female Dan Carter be his sister Sarah, or Irene van Dyk? (more…)

We congratulate our colleagues Maxine Pfannkuch, Matt Regan, Chris Wild and Nick Horton who have been recognised by the American Statistical Association for the best paper in 2011 in the Journal of Statistical Education, Telling Data Stories: Essential Dialogues for Comparative Reasoning.

This is the second major recognition on the world stage in the last year for this group, following on from their read paper before the Royal Statistical Society on World Statistics Day, 20/10/2010.

Professor David Spiegelhalter cites media’s role in dominance of emotions over statistics about travel risks

Journalists urged to ask if “the numbers make sense”

Q: So, have you seen the article about Vitamin D and diabetes?

A: Of course. The tireless staff of StatsChat read even West Island newspapers. It’s a good report, too.

Q: What did the researchers do?

A: They studied 5200 people without diabetes, following them up for five years. 199 of them developed diabetes. The people who ended up with diabetes started off with lower vitamin D levels in their blood.

Q: Where did you get those details?

A: The abstract for the study publication (you can also get the full text there free if you’re at a university or if you wait until next year).

Q: Isn’t it annoying that newspaper websites don’t provide any links to that sort of information?

A: It’s like you’re reading my mind.

Q: One of the study authors is quoted as saying “”It’s hard to underestimate how important this might be.” What do you think?

A: I think he meant “overestimate”.

Q: So, how important is this finding?

A: If it really is an effect of vitamin D, it would be really important.  A simple supplement would be able to dramatically reduce the risk of diabetes.

Q: How can we tell?

A: Someone needs to do a randomized trial, where half the participants get vitamin D and half get a dummy pill. If the effect is real, fewer people getting vitamin D will end up with diabetes.

Q: That sounds like a good idea. Is someone doing a trial?

A: Yes, Professor Peter Ebeling, of the the University of Melbourne.

Q: Is there some useful website where I can find more information about the trial?

A: Indeed.

Q: Will it work?

A: No.

Q: Are you sure?

A: No, that’s why we need the trial.  But it’s a trial of vitamin supplementation, which almost always has disappointing results, and it’s a trial  in adult-onset diabetes, which almost always has disappointing results.

Last week, in Wellington, I saw an ad warning that someone is hurt in a household accident every 48 seconds. Is that a lot?

We need some numbers. The population of NZ is about 4.5 million, and there are about 30 million seconds in a year(*).

Since I’m doing this while trying to avoid traffic in the jaywalking capital of New Zealand, let’s round off the accident rate to one every 50 seconds. That gives 600,000 accidents per year. If we had a population of six million, this would be one accident every ten years, but we only have 4.5 million, so it’s more like one accident per person per seven years.

Somehow, it sounds less impressive that way.

* For real nerds, an even more accurate approximation is π times 10 million seconds.

Stats.org has published an excellent article on the research surrounding risk factors for Sudden Infant Death Syndrome (SIDS), in particular breastfeeding:

Let there be no doubt: not breastfeeding and SIDS are correlated. The problem is that breastfeeding is correlated with many other factors as well, any of which could be the “cause” (or “causes”) behind an increased SIDS rate among people who use formula instead of mothers’ milk. These include a variety of social and cultural differences, differences in care, differences in other feeding patterns, differences in sleeping patterns, differences in genetic makeup, differences in home environment, differences in medical care, etc. The question is whether the evidence points to breastfeeding (or mother’s milk) as a preventative factor by itself and independent of all the other factors with which breastfeeding tends to go hand in hand.

It continues to unravel the statistics and evidence and concludes by saying:

Without the science, the claims of cost due to not breastfeeding – 447 babies and almost 5 billion dollars in economic loss — are like an empty bottle: wanting for real substance.

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New Zealanders will vote in a referendum in November asking whether they want to change the current voting system used for deciding the makeup of Parliament.

Dr Geoffrey Pritchard and Dr Mark C. Wilson, members of the Centre for Mathematical Social Science at the University of Auckland, have created a simulator intended to voters to compare the 5 proposed electoral systems in a quantitative way, by allowing them to compute quickly, for a given polling scenario, the party seat distribution in Parliament under each system.

You can try it out by going to http://cmss.auckland.ac.nz/2011-referendum-simulator/ and they would appreciate any feedback on how to improve it.

It is written in Javascript and the source code is publicly available. The assumptions made are detailed in the FAQ.

They hope that this will allow a better understanding of the consequences of adopting any of these systems, and complement the qualitative information given by the Electoral Commission.