Posts from January 2016 (28)

From the Herald, using data from Seek.co.nz: Pay shock: Wellington, not Auckland, is the New Zealand city with the highest advertised salaries.

According to the New Zealand Income Survey, the Wellington region has had the highest median weekly earnings for people in paid employment every year since at least 2007., so the shock should have had time to sink in by now. Looking at NZ.Stat, that’s also true for average weekly earnings.

However, when looking at actual earnings rather than advertisements at one site, Wellington’s percentage lead was only about half as big. And, of course, the actual dollar amounts are lower.

Every summer, the Department of Statistics offers scholarships to a number of students so they can work with staff on real-world projects. Katie, right, is working on the New Zealand Socio-Economic Index with Dr Barry Milne of COMPASS (Centre of Methods and Policy Application in the Social Sciences) and Professor Alan Lee from the Department of Statistics. Katie explains:

“The New Zealand Socio-Economic Index (NZSEI) assigns occupations a score that enables us to measure the socio-economic status of people in that occupation. It’s calculated using the average age, income and education level of people with each job. For example, doctors would have a very high socio-economic index, because they’re typically high-earning and well-educated people.

“The NZSEI has been created from Census data since the 90s, but has not yet been updated for the most recent Census in 2013. In this project, my job is to update the NZSEI using path analysis, and check that this updated version is appropriate for all people in New Zealand. A couple of examples include assessing that the index is valid for all ethnicities, and valid for workers in both urban and rural regions.

“The index is important to measure any changes to New Zealand over time, as it is updated with each Census. As well as this, the NZSEI uses a similar methodology to international scales, so international comparisons are possible.

“I am currently in my third year of studying Mathematics and Statistics at the University of Sheffield in England, and I’m halfway through my year here in Auckland as an exchange student. I’ve always been interested in Statistics and studying it at university level has shown me how applicable it is in a variety of fields, from finance to biology.

“Over the summer, I’m looking forward to exploring New Zealand more.”

Stuff:

The Dow Jones industrial average was set for its worst start to a year since 1932 as stock markets tanked after weak Chinese economic data reignited fears of a global slowdown.

Herald

The U.S. blue-chip index tumbled toward its worst start to a year since 1932, while banks and technology shares led the Standard & Poor’s 500 Index lower.

That’s presumably true, and bad news, but “start to a year” is doing a lot of work. Here’s the past year’s Dow:

Unless there’s something especially predictive about the first trading day of the year, this is no worse than some quite recent days. And, the Herald says further down in the story

S&P Dow Jones Indices data indicate the first day of trading has no predictive power for the rest of the year. The index ends the year in the same direction it takes on the opening day 50.6 percent of the time, the data show. The first month of the year has proved more telling — the gauge’s return in January determines its direction for the year 72.4 percent of the time.

Lateral is a relatively new science magazine produced by a bunch of mostly Australian, mostly young over-achievers. Their sixth issue is about Data.

And I think I’ve mentioned STAT, the new health and medicine (and not statistics) news site, but it’s worth mentioning again.

There’s another Herald story about incomes based on job ads at Seek.co.nz.

Data released by job search company Seek shows outside of consultancy work roles linked to the building industry were paid the most last year and were some of the few sectors to see decent pay rises.

The average salary for the construction industry is now $94,580, a boost of 5 per cent on 2013 while engineers earned an average of $92,595

Stats NZ data isn’t quite as up to date, but the NZ Income Survey, in June, found average weekly earnings in the construction industry to be $1096 (go here, and select ‘Construction’ from ‘Industry’), up about 1% from 2013 (though 5% from 2014). If you assume a full-time job with holidays, that’s $57,000 per year.

I don’t know how much of this is due to different definitions and how much is due to the Seek jobs being non-representative, but it’s possible for anyone who really cares to find out exactly what the Stats NZ number means, and that’s not true for the Seek number.

• True-colour photos of Earth from space — why it’s not as simple as that, by Emily Lakadawalla
• “The ranks of the wealthy grew in 2013, with 1.38 million households making it into the Top 1%, up from 1.36 million a year earlier.”  From CNN Money (who should understand percentages) via Felix Salmon
• Translation of international new reprints matters. The Herald had a headline “North Pole now 50 degrees above normal“, which was 50 Fahrenheit degrees. In NZ terms, just under 30 Celsius degrees.
• From the Christmas edition of BMJ, famous for its joke (but accurate) articles, a functional MRI imaging study comparing people who do and don’t celebrate Christmas, found differences in brain activation. These differences could be argued as a biological “Christmas Spirit” locus, plausible in terms of previous research.  The point, obviously, is how easy it is to overinterpret such things.
• A group in the US did a randomised, blinded trial to see what effect faster internet speeds would have: they raised the bandwidth for 1500 people from 105Mbps to 250Mbps without telling them. People used the internet more, and it wasn’t primarily the heaviest users whose use increaseed.

Every summer, the Department of Statistics offers scholarships to a number of students so they can work with staff on real-world projects. Jale, right, is exploring evolutionary relationships with Dr Steffen Klaere. Jale explains: 

“To understand the evolution of life on earth, we need to make inferences about evolutionary events leading up to the diversity of life we see now. My project is about phylogenetic inference – the set of bioinformatic tools for estimating evolutionary relationships between different species, or taxa.

“The set of taxa and their divergence is usually represented by a DNA-sequence alignment. The basic assumption is that each sequence represents a taxon and the evolutionary divergence between species is identified by differences in the respective sequences. The relatedness of taxa is then represented by a phylogenetic tree, where closely-related species are identified with leaves that are close together in the tree.

“In my project, I will investigate different statistics to assess the fitness between model and data. In particular, I am interested in identifying sites in the alignment that are not well represented by the model.

“It has been established that alignments for species with an old, most common recent ancestor will have more sites that will not inform the phylogenetic hypothesis. Such sites are often called saturated sites due to the assumption that they accumulated a lot of mutations over time. It has been hypothesised that such sites can lead to systematic error in the inference.

“That is why we want to identify influential outliers and mask them for the inference. Statistics like observed variability (OV) distances have been proposed, which are easier to compute, but tend to overestimate the number of saturated sites.

“My task will be to investigate methods that propose to identify saturated sites and test them on datasets known to suffer from systematic error. In particular, I want to test the utility of combining different statistics to address such problems.

“I am from Duelmen in Germany, but I have lived and studied in Greifswald for the past three years. I have just completed my Bachelor of Science in Biomathematics at the University of Greifswald. After this research project, I would like to pursue my Master of Science in Statistics at the University of Dortmund, also in Germany.

“What I like about statistics is that it has a wide area of use and deals with diverse topics in biology, medical science and economics. Furthermore, I like that statistics deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments. You can work together with people from different institutions and you benefit from the different knowledge they bring.

“As I have some free time over Christmas and New Year, I am thinking about travelling to the Bay of Islands to spend some time at the beaches and enjoy the beautiful countryside. After the research project, I will also have some time to travel to the South Island before flying back to Germany.”

From the Herald (from the Telegraph)

Using e-cigarettes is no safer than smoking tobacco with nicotine, scientists warned after finding the vapour damages DNA and could cause cancer.

Smoking tobacco is right up near the top of cancer risks that are easy to acquire, both in terms of how big the risk is and in terms of how strong the evidence is.

[There was some stuff here that was right as to the story in the Herald but wrong about the actual research paper, so I got rid of it. Some of the tests in the research paper used real cigarette smoke, and it was worse but not dramatically worse than the e-cig smoke]

The press release is a bit more responsibly written than the story. It describes some of the limitations of the lab tests, and makes it clear that the “no safer than smoking” is an opinion, not a finding. It also gets the journal name right (Oral Oncology) and links to the research paper.

It’s worth quoting the conclusion section from the paper. Here the researchers are writing for other people who understand the issues and whose opinion matters. I’ve deleted one sentence that’s technical stuff basically saying “we saw DNA damage and cell death”