Posts filed under Careers (25)
- Careers: The number of people getting statistics degrees in the US has doubled in the past five years (and they’re still able to get jobs)
- Increasing inequality in the US from 1977 to 2012 (it happens in other places too): top 1% share of income. The colour choice is a bit unfortunate (red: more equal, green:less equal). There are animated pictures and more inequality measures in the original
- Map of sasquatch sightings in the US. The original has all the sightings as well as this map cross-referenced with population density. Remember, just because you can measure it doesn’t mean it exists
- Software for drawing data-based maps: CartoDB. Has both free and paid versions. Worth a look if you do maps.
From One News NZ, a story about Bobby Wilcox, the team’s performance analyst, who has a PhD in Statistics from our department
She’s been one of the Silver Ferns most integral members for nine years, yet she’s largely anonymous outside…
[the video comes with a very annoying ad, sadly]
From this morning’s Twitter feed
- An animated GIF (click on it to wake it up) showing how to improve a barchart by removing junk. [from Darkhorse Analytics: Data looks better naked]
- Data journalism: how the data sausage gets made. Jacob Harris describes how he collected and summarised data on meat recalls in the US
- The Royal Statistical Society has repeated the simple maths test they gave politicians last year, this time for senior professionals and managers. Less than half of them could give the probability of getting two heads from tossing two coins.
- However, the same Royal Statistical Society news item ends “The figures have been weighted and are representative of all GB adults (aged 18+)”. This seems to me to fall in the “not even wrong” category. The target group aren’t remotely representative of all British adults, and I’d be surprised if it was even possible to reweight them to the national age distribution.
- Cathy O’Neill (mathbabe.org) asks why rankings of eg, cars or universities don’t allow the user to change priorities for different attributes (as the OECD Better Life Index does, for example)
Deciding who to interview: Aline Lerner looked at resumes of 300 candidates interviewed at a Silicon Valley company to see what predicted getting the job. The biggest factor wasn’t grades or degree or experience, it was typos – and this was among people who got an interview.
We looked at tens of thousands of interviews, and everyone who had done the interviews and what they scored the candidate, and how that person ultimately performed in their job. We found zero relationship. It’s a complete random mess, except for one guy who was highly predictive because he only interviewed people for a very specialized area, where he happened to be the world’s leading expert.
From the US 6th Circuit Court of Appeals (PDF), in a lawsuit alleging false advertising by a US law school, based on a low-quality survey of graduates
For example, the Employment Report for 2010 states that the “average starting salary for all graduates” was $54,796. On its face, the phrase “all graduates” means just that: all Cooley graduates—not just the ones who responded to the survey—made, on average, $54,796. One could assume that, because there were 934 graduates, the average starting salary for all 934 graduates was $54,796. The title of the document containing this statement is “Employment Report and Salary Survey.” Therefore, it cannot be that the average starting salary of all 2010 graduates was $54,796, because the document, entitled “Employment Report and Salary Survey” (emphasis added) was not based on the responses of all of the Cooley graduates in 2010; rather, the document states that the number of 2010 graduates was 934, but the number of graduates with employment status known was 780. So, the “[a]verage starting salary for all graduates” would instead mean the average starting salary of graduates who responded to the survey and chose to include their salary information—not the average salary of all Cooley graduates in any given year.
We agree with the district court that this statistic is “objectively untrue,” but that the graduates’ reliance upon it was “also unreasonable,” which dooms their fraudulent misrepresentation claim.
It’s not just statisticians who think you need to pay attention to where the numbers come from.
If you believe the numbers, it looks as though analytics is way ahead in the synonym game, followed by data science, but at least statistics is still ahead of business intelligence. And at least this is a bar chart, though not an index in any usual sense of the term.
The company describes Big Data as having ‘fueled one of the most hyper-growth niches of employment in a century’, but since their projection is for the sector to grow to nearly 1% of the US job market by 2015, we clearly need to be careful of the definition of fast growth
This is a common question from our students. Unfortunately our perspective does not always lend itself easily to life outside of research and academia, as what I look for in a curriculum vitae and in a job interview is usually with respect to hiring someone who will become an academic staff member. However, fellow statistician, and the Young Statisticians representative for the New Zealand Statistical Association executive committee, Kylie Maxwell has posted her own experience as part of the International Year of Statistics.
Rafa Irizarry at Simply Statistics has a longish piece on the future of applied statistics:
Despite having expertise only in music, and a thesis that required a CD player to hear the data, fitted models and residuals , I was hired by the Department of Biostatistics at Johns Hopkins School of Public Health. Later I realized what was probably obvious to the School’s leadership: that regardless of the subject matter of my thesis, my time series expertise could be applied to several public health applications. The public health and biomedical challenges surrounding me were simply too hard to resist and my new department knew this. It was inevitable that I would quickly turn into an applied Biostatistician.
It makes a nice change from the people worrying that computer science will beat us up and steal our lunch.