Last week we had the pleasure of Professor Stephen Pollock (University of Leicester) visiting our Department, best known in academic circles for his work on time series filtering (see his papers, and his excellent book). But he has another career as a member of the UK House of Lords (under the name Viscount Hanworth — he is a hereditary peer). It made me wonder how many other politicians have PhDs (or equivalent) in statistics, or at least in mathematics. I realise that a lot of mathematicians before the 20th century were often involved in politics, in one way or another, especially in France. Also, the notion of a PhD is a relatively recent invention. But if we restrict the time to 1950 onwards, there must be quite a few politicians with doctorates in the mathematical sciences.
Posts Tagged ‘mathematics’:
We are currently advertising for three academic positions, suitable for recent PhD graduates. Lecturer (Applied Statistics or Operations Research) Five-year position with MAXIMA and the School of Mathematical Sciences Two positions available. Applications close 31 October. More information. Lecturer (Econometrics/Business Statistics) Continuing position with the Department of Econometrics and Business Statistics Applications close 31 January 2014. More information. Please don’t send any questions to me. Click the “More information” links and follow the instructions.
The publishing platform I set up for my forecasting book has now been extended to cover more books and greater functionality. Check it out at www.otexts.org.
The “Monash Academy for Cross and Interdisciplinary Mathematical Applications” (MAXIMA) is a new research centre that aims to maximise the potential of mathematics to deliver impact to society. It will be led by Kate Smith-Miles. I will also be involved along with several other mathematicians at Monash. Our mission at MAXIMA is to find solutions to 21st century problems by dismantling mathematical barriers. MAXIMA will be launched on 25 September at a public lecture on “The Role of Embedded Optimization in Smart Systems and Products”. More details at community.monash.edu/maxima
These terms get confused all the time (e.g., this question on CrossValidated.com), and so I thought it might be helpful to try to summarize the distinction and some of the associated models.
For students who are interested in doing a PhD at Monash under my supervision. First, read the instructions on how to apply. Second, poke around my website to see the sorts of topics I work on. There’s no point asking to do a PhD with me if you want to do research on something I don’t know much about. In particular, please note that I’m not really interested in finance or economics. There are some excellent researchers at Monash on both topics, but I’m not one of them. If you’re still interested, here is what I normally expect. You should have a strong background in statistics or econometrics (at least honours or Masters level) along with some mathematics and computing. It is essential that you have studied some matrix algebra, multivariate calculus and optimization. You should be capable of programming with a high level language such as R or Matlab; if you can write in C as well, even better. Students who struggle either find they don’t know enough mathematics (or didn’t pay attention when they learned it), or they don’t know enough computing. I don’t expect students to be whiz programmers, but I do expect them to know about for loops, if statements, local variables and functions, and I assume they have some idea about nonlinear
DLMF For nearly 50 years, a standard reference in mathematical work has been Abramowitz and Stegun’s (1964) Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. It has provided a marvellous collection of results and tables that have been indispensable for a generation of mathematicians. I’ve used it to look up computationally efficient methods for calculating Bessel functions or gamma functions, or to find one of those trigonometric identities I learned in high school and no longer remember. Apparently nearly 1 million copies of the handbook have been printed and it has also been scanned and put online. Lately, the handbook has fallen out of favour a little, partly because there is not such a need for it. We no longer need tables for trigonometric functions or logarithms, and a lot of functions are built into R, including Bessel functions and variations on the gamma function. Another reason for its declining popularity has been the rise of online resources: if you want to know something about orthogonal polynomials, there is a good chance it is covered in the Wikipedia article. Now the handbook has been reissued as the NIST Handbook of Mathematical Functions (Cambridge University Press) with a free web edition called the NIST Digital Library of Mathematical Functions (DLMF).