Stats Chat

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 June 29 2012.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 23-29 2012 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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Team Ratings for Round 16

Here are the team ratings prior to Round 16, 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 110 matches played, 66 of which were correctly predicted, a success rate of 60%.

Here are the predictions for last week’s games.

Predictions for Round 16

Here are the predictions for Round 16

A fairly large fraction of the spam advertising the chance to capitalise on stolen riches is sent by Nigerian criminals.  What should be more surprising is the fact that a lot of the spam actually says it’s from Nigeria (or other West African nations).  Since everyone knows about Nigerian scams, why don’t the spammers claim to be from somewhere else? It’s not as if they have an aversion to lying about other things.

A new paper from Cormac Herley at Microsoft Research has a statistically-interesting explanation:  the largest cost in spam operations is in dealing with the people who respond to the first email.  Some of these people later realise what’s going on and drop out without paying; from the spammer’s point of view these are false positives — they cost time and money to handle, but don’t end up paying off.   A spammer ideally wants only to engage with the most gullible potential victims; the fact that ‘Nigeria’ will spark suspicions in many people is actually a feature, not a bug.

League tables work well in sports.  The way the competition is defined means that ‘games won’ really is the dominant factor in ordering teams,  it matters who is at the top, and people don’t try to use the table for inappropriate purposes such as deciding which team to support.  For schools and hospitals, not so much.

The main problems with league tables for schools (as proposed in NZ) or hospitals (as implemented in the UK) are, first, that a ranking requires you to choose a way of collapsing multidimensional information into a rank, and second, that there is usually massive uncertainty in the ranking, which is hard to convey.   There doesn’t have to be one school in NZ that is better than all the others, but there does have to be one school at the top of the table.  None of this is new: we have looked at the problems of collapsing multidimensional information before, with rankings of US law schools, and the uncertainty problem with rates of bowel cancer across UK local government areas.

This isn’t to say that school performance data shouldn’t be used.  Reporting back to schools how they are doing, and how it compares to other similar schools, is valuable.  My first professional software development project (for my mother) was writing a program (in BASIC, driving an Epson dot-matrix printer) to automate the reports to hospitals from the Victorian Perinatal Data Collection Unit.  The idea was to give each hospital the statewide box plots of risk factors (teenagers, no ante-natal care), adverse outcomes (deaths, preterm births, malformations), and interventions (induction of labor, caesarean section), with their own data highlighted by a line.   Many of the adverse outcomes were not the hospital’s fault, and many of the interventions could be either positive or negative depending on the circumstances, so collapsing to a single ‘hospital quality’ score would be silly, but it was still useful for hospitals to know how they compare.  In that case the data was sent only to the hospital, but for school data there’s a good argument for making it public.

While it’s easy to see why teachers might be suspicious of the government’s intentions, the rationale given by John Key for exploring some form of official league table is sensible.  It’s definitely better not to have a simple ranking, and it might arguably be better not to have a set of official comparative reports, but the data are available under the Official Information Act.  The media may currently be shocked and appalled at the idea of league tables, but does anyone really believe this would stop a plague of incomplete, badly-analyzed, sensationally-reported exposés of “New Zealand’s Worst Schools!!”?  It would be much better for the Department of Education to produce useful summaries, preferably not including a league-table ranking, as a prophylactic measure.

Thanks to those who nominated in last week’s Stat of the Week competition.

This week we’re awarding Lindsay Mitchell’s nomination of the NZ Herald’s editorial which stated that “The vast majority of child abuse is perpetrated by men.”

There are numerous official sources that disprove this claim. For instance: Fig 7. Number of female and male abusers of specific types of abuse and neglect 2006 (pg 117) and Apprehensions for assault on a child (pg 10)

This isn’t a new bad stat, but keeps cropping up in the media.

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 June 22 2012.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 16-22 2012 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.
(more…)

Team Ratings for Round 15

Here are the team ratings prior to Round 15, 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 103 matches played, 61 of which were correctly predicted, a success rate of 59.22%.

Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 15

Thanks for all those who nominated in last week’s Stat of the Week competition.

This week we’re awarding Nick Iversen’s nomination of the NZ Herald’s article “CEO Pay Survey: Salaries stall for NZ’s top bosses” with some nice re-analysis:

The Herald says “the value of the average chief executive pay packet has dropped” and quote the drop in average pay as 0.4%

That’s one way of looking at the data. Here’s another way:

Of the CEOs surveyed 13 had drops in pay and 22 had pay rises. The median pay drop was 7%, the median pay rise was 18.5%.

Of if you prefer mean the mean pay drop was 13.5%, the mean pay rise was 26%.

So most of them had pay rises and the rises were higher than the drops. Looks to me as if the CEOs had a very good year.

One might argue that that this is just an arithmetic blunder, but it does raise (the usual) questions of means and medians.

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 June 15 2012.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 9-15 2012 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.
(more…)

May 14, NZ Herald:  Housing boom cuts mortgagee sales.  The number of mortgagee listings has been falling nationally since the recession, and Auckland is leading the charge.

May 31: Stuff: More people losing the family home.  High numbers of ”mum and dad” homeowners are losing family homes to mortgagee sales, new figures show.

June 1: Stuff: Rise in family home mortgagee sales. Family homes are making up an increasing number of the more than 2200 mortgagee sales in New Zealand, new figures show.

June 9: NZ Herald: Mortgagee sales: Landlords feel pain. Mortgagee sales have hit record numbers, and landlords are the new victims.

The housing market doesn’t change that much from week to week.