Stats Chat

Team Ratings for Wednesday Game for Round 5

The basic method is described on my Department home page.
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 38 matches played, 27 of which were correctly predicted, a success rate of 71.1%.
Here are the predictions for last week’s games.

Predictions for Wednesday Game for Round 5

Here are the predictions for Wednesday Game 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.

MPs expenses paid by the Parliamentary Service were published recently for the quarter ending June 30. Here are the averages by party (click to embiggen)

This is a terrible presentation of the data, though not the worst one I saw.  Simple bar charts like this are sometimes useful, but can be very misleading. Here’s a dotplot, showing the individual data points

In this version, you should immediately notice something. There are a lot of Labour MPs who aren’t getting any expenses! This might then prompt  you to go back to the website and read the “Understanding members’ expenses” page, and find out that these numbers don’t include Ministers’ expenses.  Most of the ministers are in the Labour Party (for some reason) and that will pull down the average.

You might then remove the ministers and compare averages again, but it’s not obvious that’s a good comparison. The outlying blue dot at the top there is Chris Luxon. It seems reasonable that the leader of the opposition could have more expenses than a random MP.  This then raises the question of whether comparing averages for non-Minister MPs between the government and opposition is sensible in general.  There are other questions: for example,  travel expenses will depend on where you live as well as where you go.  While we’re looking at outliers, I should also note the outlying blue dot at the bottom. That’s Sam Uffindell. He was elected in a by-election on June 18, so he didn’t have much time to rack up expenses.

Team Ratings for Week 5

The basic method is described on my Department home page.
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 31 matches played, 21 of which were correctly predicted, a success rate of 67.7%.
Here are the predictions for last week’s games.

Predictions for Week 5

Here are the predictions for Week 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 25

The basic method is described on my Department home page.
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 184 matches played, 128 of which were correctly predicted, a success rate of 69.6%.
Here are the predictions for last week’s games.

Predictions for Round 25

Here are the predictions for Round 25. 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 Wednesday Game for Round 4

The basic method is described on my Department home page.
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 30 matches played, 20 of which were correctly predicted, a success rate of 66.7%.
Here are the predictions for last week’s games.

Predictions for Wednesday Game for Round 4

Here are the predictions for Wednesday Game for Round 4. 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.

News.com.au has the headline New report from Westpac reveals ‘turbocharged’ spending and increased dependence on antidepressant drug, and follows it up with “A new report looking at Australia’s spending on health services shows one drug entered the ‘Top 10’ list of prescription medicines for the first time in 14 years.”  The article then goes on about using Westpac card data and a survey of pharmacies. I saw this on Twitter, where someone was outraged that Westpac was using individual drug purchase data this way. They’re not.

There’s literally nothing in the article, or the press release it’s based on, or the report that’s based on to support “increased dependence on antidepressant drug”, and not much to support increased use. The information on sertraline prescriptions didn’t come from the Westpac survey. The news about sertraline entering the top ten prescribed medicines is from the Pharmaceutical Benefit Scheme (Australia’s version of Pharmac), who (like Pharmac) release this sort of data every year. In the year 2019-2020, sertraline was one of the top ten; it hadn’t been in previous years. This isn’t a new report; it came out in late 2020 and we already have the data for 2020-21.  Moving into the top ten doesn’t necessarily imply higher use, and we can’t tell from these data whether the prescriptions for antidepressants in general increased or whether the relative use of different antidepressants changed.

The actual Westpac survey information is probably interesting if you run a pharmacy in Australia, but it doesn’t have much headline potential.

Team Ratings for Round 24

The basic method is described on my Department home page.
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 176 matches played, 121 of which were correctly predicted, a success rate of 68.8%.
Here are the predictions for last week’s games.

Predictions for Round 24

Here are the predictions for Round 24. 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 Week 4

The basic method is described on my Department home page.
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 23 matches played, 15 of which were correctly predicted, a success rate of 65.2%.
Here are the predictions for last week’s games.

Predictions for Week 4

Here are the predictions for Week 4. 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 Week 3

The basic method is described on my Department home page.
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 16 matches played, 11 of which were correctly predicted, a success rate of 68.8%.
Here are the predictions for last week’s games.

Predictions for Week 3

Here are the predictions for Week 3. 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 1News on Twitter — with the text “Do these stats make you mad? Pay attention – for every $100 a man earns in NZ, a woman doing the same job earns $8 less.”

As Graeme Edgeler says, the linked article does not substantiate the claim in the text of the tweet at all. The $8 number isn’t referenced in the article and the 9.2% number doesn’t measure earnings differences for two people doing the same job.  It’s also worth considering a second article about the new income statistics linked from the first article. It gives yet another pair of income numbers for men and women, one where the gap is 25% and is slightly smaller than last year.  On top of that,  the 10% and 9.2% claims in the image seem to be about two different income measures, though it’s not really clear where the 10% is sourced.  I’ll also link the new StatsNZ figures, which 1News doesn’t bother to do.

Let’s start with the gender pay gap.  Stats New Zealand’s indicator for gender pay differences is the percentage difference in median hourly earnings.  They have a nice document from 2015 explaining why they define it this way. It’s not a perfect summary — it’s not going to be; it’s a single number — but it’s what they use.  A gender pay gap of 9.2% means that if median hourly earnings for men were $100 (sadly, no) they would be $90.80 for women.  That’s not $8 less; it’s $9.20 less.  The $8 figure doesn’t seem to come from anything in the article, and it’s an understatement of the gap, which is a bit unusual.

Not only is the figure of $8 apparently wrong, the interpretation is wrong.  The gender pay gap isn’t about comparing income for  the same job. That’s good, because a significant part of gender discrimination in pay comes from women’s jobs being paid less.  Looking at the exact same job would understate the pay gap, and would get you into endless arguments over, eg, whether “captain of the national rugby union team” was or was not the same job for Sam Cane and Ruahei Demant.  The interpretation is also wrong because another reason women earn less money than men is they tend to work fewer hours, and that’s not included in the pay gap.

The second linked article discusses median weekly earnings. It has figures of $1320 for men and $1055 for women, a 25% gap.  The increase in median weekly earnings for the population as a whole was 8.8%, which is the only whole-population percentage increase in either article, so it seems like it should be the basis for “we’re all earning nearly 10% more than last year”.  If you dismiss the ‘all’ as journalistic license, and rephrase as “a typical person” then I suppose 8.8% is nearly 10%, but it’s further from 10% than 9.2% is.

Given how different the gender pay gap is when you compute it in different ways, you might  wonder if international comparisons use StatsNZ’s preferred definition. They don’t.  The OECD restricts to people working full time:  hourly and weekly earnings will have the same gaps, but you’ll miss out the pay gap due to more women working in part time jobs.  By the OECD definition, the New Zealand gender pay gap is 6.7% for employees and 30.8% for self-employed people.

The article linked to the tweet is about a campaign to make large businesses disclose their gender pay gap.  I’m fairly generally in favour of this sort of transparency, but when major news outlets seem to not understand or not care what the number means, publicising it might not be as effective as you’d like.