Posts filed under Education (86)

From the Herald (taken from the Daily Mail)

Volunteering is good for the heart as well as the soul, researchers say.

In fact, the research didn’t examine either the soul or the heart, but they did look at weight, cholesterol, and biochemical measurements related to inflammation.

The study, published in the journal JAMA Pediatrics, tested 106 teenagers from Vancouver. Those involved in altruistic activities had lower levels of cholesterol and inflammation.

The paper is here, and even if you can only see the abstract, you can see the story missed an important issue. This was actually a randomised trial:

Intervention  Weekly volunteering with elementary school–aged children for 2 months vs wait-list control group.

That is, the researchers took all the students from a high school in western Canada (presumably Vancouver, though it doesn’t say).  These students are required to do some volunteer work as part of the standard curriculum, and they were randomised to do it in first or second semester.

The article doesn’t address the possibility that the volunteering might have involved an increase in exercise: even just at the level of standing up and moving around vs sitting in front of a screen.  Also, as the researchers admit, this is a very small study, intended as a pilot for larger-scale research, and they may just have been lucky.  It’s still interesting to see the reductions in cholesterol and biochemical markers of inflammation.

There has been (justified) wailing and gnashing of teeth over recent year-9 maths comparisons, and the Herald reports that a `back to basics’ system is being considered

Auckland educator Des Rainey, who did the research with teachers to test his home-made Kiwi Maths memorisation system, said the results came as a shock to the teachers and made him doubt his programme could work.

But after a year of practising multiplication and division on the Kiwi Maths grids for up to 10 minutes a day, the students more than doubled their speed.

This program looks promising, but why is anyone even talking about implementing a major nationwide intervention based on a small, uncontrolled before/after comparison measuring a surrogate outcome?

That is, unless you believe teachers and schoolchildren are much less individually variable than, say, pneumococci, you would want a randomised controlled comparison, and since presumably Des Rainey would agree that speed of basic arithmetic is important primarily because it’s a foundation for actual numeracy, you’d want to measure the success of the program based on numeracy tasks rather than on arithmetic speed. The results being reported are what the medical research community would call a non-randomised Phase IIa efficacy trial — an important stepping stone, but not a basis for policy.

Of course, that’s not how education works, is it?

Generally good use of survey data in a story from Stuff about the embattled Education Minister.  They even quote a competing poll, which agrees very well with their overall statistic.

The omission, though, relates to the headline figure: “71pc want Parata gone – survey”.  That’s a proportion “among voters from Canterbury”.   Assuming that they don’t mean “voters” in any electorally-relevant sense, just respondents, we would expect about 120 of the 1000 respondents to be from Canterbury. The maximum margin of error is a little under 10%.

The fact that one region has 71% wanting Ms Parata gone when the overall national average is 60% would actually not be all that notable on its own. Since we already expect her to be less popular in ChCh, the difference is worth writing about, but if it’s worth a headline, it’s worth a margin of error.

Do you shout at the morning radio when a story about a medical “risk” is distorted, exaggerated, mangled out of all recognition? You are not alone. Kevin McConway and David Spiegelhalter, writing in Significance, a quarterly magazine published by the Royal Statistical Society, have come up with a checklist for scoring media stories about medical risks. Their mnemonic checklist comprises 12 items and is called the ‘John Humphrys’ scale, said Mr Humphrys being a well-known UK radio and television presenter.

They assign one point for every ‘yes’ and do a test on a story about magnetic fields and asthma, and another about TV and length of life. The article, called Score and Ignore: A radio listener’s guide to ignoring health stories, is here.

Could form the basis of a useful classroom resource.

Polls and surveys making various claims land on journalists’ desks every day – but not all of them are newsworthy (and the bogus, PR-driven ones that make it into print are subsequently shredded in this very forum).

The statschat.org.nz team is always keen to help people understand the difference between a reliable poll and something that should be filed in the bin. So we’re delighted that two members of the statschat.org.nz team, Andrew Balemi, a polls and surveys expert from the Department of Statistics at The University of Auckland, and adviser Julie Middleton have been given an hour at this Wednesday’s Journalists Training Organisation/Journalism Education Association conference to talk about polls and surveys.

They’re not going to each anyone to crunch numbers. What’s far more important is knowing the right questions to ask about a poll or survey to determine whether it should be taken seriously.

This is the hand-out we are providing – we have only an hour, so the list of questions isn’t complete, but it gives you an idea of how we encourage journalists to think.

Questions a reporter should ask of a poll or survey

Why is the poll/survey being done?
What do the pollsters want to find out?

Who is doing the survey?
Who paid for the survey?
Who carried out the work?
Is the person/company that carried out the survey a member of the Market Research Society of New Zealand? (ie, is it subject to a code of ethics?)

What we’re looking for: Evidence of lobbying, misinformation, public-relations or marketing spin … or just a company hoping to get editorial when it should buy an ad.

How representative is the sample?
How were those to be polled/surveyed chosen?
From what area (nation, state, or region) or group (teachers, National voters etc) were these people chosen?
How were the interviews conducted? (Internet survey, face-to-face, by phone)…

What we’re looking for: Evidence that the poll/survey is based on a genuinely representative random sample and has been conducted according to sound statistical principles. Be wary if you can’t get the original research questionnaire, raw data and a full explanation of methods.

If possible, ask about the broader picture
Does this study reflect the findings of other polls/surveys on this topic?

What we’re looking for: Evidence of similar findings elsewhere. 

Is this poll/survey worth reporting?
If you get positive responses to the above, yes. If not, this question becomes a philosophical one: Do you ignore accuracy for a sexy subject? Or run a story based on a bogus survey with a long list of caveats?

Don’t be afraid to ask professional statisticians for advice and help. They will generally be flattered – and pleased that you are taking such care.

The Auckland Mathematical Association and our Department of Statistics ran a special event at The University of Auckland’s Tamaki campus for 350 Year 13 statistics teachers last Thursday. The workshop introduced teachers to a range of online and interactive tools and resources to support the new statistics curriculum, which starts in the 2013 school year.

The workshop will be repeated in Wellington, Christchurch and Dunedin, with local maths associations running each event. You can find out more about the statistics road tour herephotos and teacher quotes here.

Jason Ellwood of Otumoetai College talks bootstrapping at The University of Auckland Statistics Roadshow, Tamaki campus, Thursday 22 November 2012. Photo: Stephen Barker/Barker Photography, www.barkerphotography.co.nz
©The University of Auckland.

Proving that adding words to an algebra problem doesn’t automatically give it real-world context:

From Intriguing Mathematical Problems, Dover Publications, and Dan Meyer

Thanks, Textbooks adds: This brings up several more important questions:

• Who has a “favorite” orange?
•  How long have you had this orange that you’ve bonded with it so much?
• Who has an equation to calculate the weight of an orange?
• Is it your favorite because it happens to weigh nine pounds!?

(via)

[Other observations from Thanks, Textbooks  include:  I’m less concerned with the question, “What does the scale read?”  and more concerned with the question, “Why the hell are we lubricating a hamster?”]

It’s the end of another semester, and we’re about to have a couple of days of presentations by our BSc(Hons) and MSc students, telling us what they’ve been doing all year:

Improving staffing schedules at a Cardiothoracic Intensive Care Unit

Clickers: A study of student opinion on audience response technology

Population modelling interactions between introduced and threatened species for conservation management 

Deal or No Deal

From question to design: Creating a guide for experimental planning and design in the biological sciences 

Balanced Incomplete Block Design in Multivariate Analysis

Use of multivariate omnibus test with mixed model analysis on heterogeneous nested data

Generalised Estimating Equations (GEEs) in the multivariate omnibus test

Web-based interactive graphics

Interactive Graphics for Data Quality Assessment

Creating an R meta-analysis graphics package

Monte Carlo Methods for Adjusting Confidence Intervals for Parameter of Point Process Models

Investigating if follow-up at outpatient clinics helps prevent adverse patient outcomes from Bowel Resection and Hip Replacement 

Methods of analysing hospital length of stay

Data management for combining data sets and macro simulation

Bootstrap methods in linear regression

Comparison of volatility estimates in Black-Scholes option pricing

Financial planning for retirees

A diagnostic for the Gaussian copula

Model Selection under Complex Sampling

BART vs Logistic regression: Propensity score estimation

Modelling and Prediction of Electricity Consumption

Brand attribute importance using choice elimination

Stuff is reporting “Food and learning connection shot down”,based on a local study

Researchers at Auckland University’s School of Population Health studied 423 children at decile one to four schools in Auckland, Waikato and Wellington for the 2010 school year.

They were given a free daily breakfast – Weet-Bix, bread with honey, jam or Marmite, and Milo – by either the Red Cross or a private sector provider.

My first reaction on reading this was: why didn’t they take this opportunity to do a randomised trial, so we could actually get reliable data.  So I went to the Cochrane Library to see what randomised trials had been done in the past. These have mostly been in developing countries and have found improvements in growth, but smaller differences in school performance.

Then I tried asking the Google, and its second link was a paper by Dr Ni Mhurchu, the researcher mentioned in the story, detailing the plans for a randomised trial of school breakfasts in Auckland.  At that point it was easy to find the results, and see that in fact Stuff is talking about a randomized trial. They just didn’t think it was important enough to mention that detail.

To the extent that one can trust the Stuff story at this point, there seem to be three reactions:

• I don’t believe it because my opinions are more reliable than this research
• Lunch would work even if breakfast didn’t
•  We should be making sure kids have breakfast even if it doesn’t improve school performance.

The latter two responses are perfectly reasonable positions to take (though they’re more convincing where they were taken before the results came out).  School lunches might be more effective than breakfasts, and the US (hardly a hotbed of socialism) has had a huge school nutrition program for 60 years.

Still, if we’re going to supply subsidised meals to school kids, we do need to know why we’re doing it and what we expect to gain.    This study is one of the first to go beyond just saying that the benefits are obvious.

From Frances Woolley at the economics blog ‘Worthwhile Canadian Initiative’

Canada’s 2005 National Graduates Survey asked respondents the following question: “Compared to the rest of your graduating class in your field(s) of study, did you rank academically in the top 10? Below the top 10% but in the top 25%…”