Posts from October 2015 (50)

There are useful pieces by David Fisher in the Herald, and Tom Pullar-Strecker at Stuff, about the new NZ Data Futures Partnership and its chair, Dame Diane Robertson.  The idea is that the government has access to a lot of data, which could be used in all sorts of ways, but that New Zealand society needs to make decisions about which uses are ok. At least, that’s the idea in David Fisher’s story. In the Stuff piece it sounds more as though the idea is to educate people so they agree with the desired uses. [update: in the print version of the Herald there’s also something by Harkanwal Singh on the social consent issue]

Detailed individual data can be used for predicting things, and while there’s obviously a problem if the predictions are inaccurate, there can be even more of a problem if they are accurate. The Herald story mentions the use of predictions of re-offending to give people longer prison terms, so-called ‘evidence-based sentencing‘.

It isn’t just a question of whether data will be used to do Bad Things, though. There’s a broader problem of maintaining trust in government data. If you think your information is going to be used to do complex, mysterious, and potentially creepy things, you’re going to be less likely to talk to the nice StatsNZ interviewer.  Reliable government data collection is important for the private sector as well as the public sector, and it’s much more difficult and expensive if the public don’t trust the data collectors.

In the US, according to a recent analysis, confidence in federal statistical agencies is fairly low — they’re rated more highly than the politicians, but below the military and universities, and level with newspapers.

In this survey, it mattered how much people knew about the statistical agencies, but in a complicated way. For people who didn’t know much about what the agencies did, confidence in them was moderately well correlated with confidence in the military, newspapers, Congress, and universities. For people who knew more about the agencies, these correlations were weaker.  These people might like or dislike the Census Bureau or the CDC, but didn’t see the agencies as part of a vague and powerful Them.

There are plenty of cynical explanations you can give for these results, but there’s also an obvious positive explanation: it’s good for people to understand what government does with their data and why.

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 October 23 2015.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of October 17 – 23 2015 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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If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

I was surprised to see a headline in the Business section of the Herald saying “2015 luckiest year for Lotto players” about lotto jackpots (story here)

After all, the way the lottery jackpots work, the amount paid out is a fixed fraction of the amount taken in. If there are more people winning large amounts then either the large amounts aren’t as large as in other years, or it’s because more people are collectively losing large amounts. Lotto players, considered individually, can be lucky or not; lotto players conside collectively, can’t be.

If you look carefully, though, you can see this isn’t a news story. It’s a “Sponsored Story”.

This still seems different from the “Brand Insight” that “connects readers directly to the leadership thinking of many prominent companies and organisations“, or the science and technology column by Michelle ‘Nanogirl’ Dickinson that was initially sponsored by Callaghan Innovation.

• With some insurance companies taking advantage of exercise trackers like FitBit to discriminate in favour of the health, there’s a potential market for fooling your FitBit. It’s hard to tell if UnfitBits is serious, but someone will be.

• When you might not want the government to have high-quality evidence-based choice of policies

• The pitfalls of using Google n-grams for linguistic research, from Wired
  

• The Sveriges Riksbank Prize in Economic Sciences in memory of Alfred Nobel went to Angus Deaton. Here’s a readable example of his writing, on why the poverty line is the same everywhere in the US.

Team Ratings for the Quarter Finals

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 Rugby World Cup.

Performance So Far

So far there have been 40 matches played, 34 of which were correctly predicted, a success rate of 85%.
Here are the predictions for last week’s games.

Predictions for the Quarter Finals

Here are the predictions for the Quarter Finals. The prediction is my estimated expected points difference with a positive margin being a win to the first-named team, and a negative margin a win to the second-named team.

Team Ratings for the ITM Cup Finals

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 7 matches played, 5 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for the ITM Cup Finals

Here are the predictions for the ITM Cup Finals. 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 SemiFinals

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 40 matches played, 29 of which were correctly predicted, a success rate of 72.5%.
Here are the predictions for last week’s games.

Predictions for the SemiFinals

Here are the predictions for the SemiFinals. 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.

One News had a story tonight about elephants. This is how it starts

NZ anchor: An American researcher thinks he may have come up with a new weapon in the fight against cancer, inspired by a trip to the zoo. He remembered that elephants almost never get cancer and wondered whether what protects them could also help us.

US reporter: Elephants have survived 55 million years on this earth. They’ve evolved to beat cancer, and they might just help us beat it too

That’s a nice story, but it’s basically backwards from the more-plausible story in Nature News, and the (open-access) paper in JAMA.

The distinctive feature of elephant blood, according to either version of the story, is that elephants have many more copies of the tumour-suppressor gene p53. This gene makes a key protein in the mechanism that causes cells with DNA damage to kill themselves rather than reproducing and turning into tumours.  A large proportion of tumours have mutations in p53, and people who inherit a damaged copy of the gene tend to develop cancer (including some unusual forms) early in life.  We’ve known about p53 for a long time — decades — so while it is a target for drug development, it isn’t by any means a new target.  We haven’t got far with it because it’s hard to mimic the effect of a protein that acts inside the cell nucleus.

The story in Nature News is that the American researcher, Dr Jordan Schiffman, specialises in treating children with familial cancer, including ones who have inherited mutations in p53 (Li-Fraumeni syndrome). He heard a talk about elephants having many copies of p53. He then went to his local zoo to find out what the cancer rate was in elephants, and confirmed it was low.   This is important;  lots of people will tell you that sharks, for example, don’t get cancer, and that’s just not true.  Elephants, on the other hand, really do seem to have a surprisingly low rate of cancer.

Since elephants have a lot of cells and live a long time, you’d expect them to have a lot of chances to get cancer. Studying elephants makes sense as a way to find completely new ways of treating or preventing cancer. Unfortunately, it seems that a major reason elephants don’t get cancer  is that they have lots of redundant p53 genes, which isn’t a new treatment target. (Other reasons may be that they don’t smoke and they eat vegetarian diets.)

So, while it’s true that elephants have multiple copies of the p53 gene, everything else in the story is basically backwards. Looking for new cancer treatment targets in elephants is a good idea, but that’s isn’t quite what they did. The findings are good news for elephants but they are bad news for us; p53 isn’t a promising new treatment target, it’s one of the oldest ones we have.

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 October 16 2015.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of October 10 – 16 2015 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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