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  • 27 Feb 2018
    Angus Macdonald

    Everything Points to Poisson

    One recurring theme in our forthcoming book, Modelling Mortality with Actuarial Applications, is the all-pervading role of likelihoods that suggest the lurking presence of a Poisson distribution.  A popular assumption in modelling hazard rates is that the number of deaths observed at any given age is a Poisson random variable, so perhaps that might explain […]

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  • 26 Feb 2018
    Ian Thompson

    What makes an expert?

    In days of 8-bit computers, one would sometimes encounter individuals who knew everything about a particular device or piece of software. Single programmers wrote entire applications or games, and some could debug their work by looking directly at a core dump (a printout of the numbers stored in the computer’s memory). Some even managed to […]

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  • 5 Feb 2018
    Joppe W. Bos, Arjen K. Lenstra

    A Tribute to Peter L. Montgomery

    Peter L. Montgomery's contributions to computational number theory had a direct impact on our day-to-day information security life. In their new book, Joppe W. Bos and Arjen K. Lenstra elaborate on Montgomery's lasting impact.

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  • 28 Nov 2017
    Tandy Warnow

    Computational phylogenetics for algorithms designers

    Phylogenetic trees and multiple sequence alignments are used in many biological analyses, including protein structure and function prediction, microbiome analysis, and the inference of human migrations. Yet, constructing these trees and alignments turns out to be much more difficult than expected on large datasets. Tandy Warnow explores these difficulties and how algorithm designers can best develop new methods to address these issues.

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  • 8 Nov 2017
    Tony Hey

    Ada Lovelace Programming Pioneer

    For the 150th anniversary of Marie Curie's birth Tony Hey author of The Computing Universe, 2015 looks at the life and legacy of the first computer programmer Ada Lovelace.

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  • 1 Sep 2017
    Trent Lalonde, Jamie Riggs

    To use, or not to use, ANOVA?

    What do you do when faced with analyzing student ratings from 1 to 5 for 3 instructors in 3 classes? Aside from questioning the validity of students assessing instructor capability other than for the income generated by high enrollments, and that this is but a toy example, many naive analysts turn to the well-known analysis […]

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  • 26 May 2017
    Guy Thomas

    Insurance and adverse selection: counter-argument

    My previous blog summarised the orthodox argument why adverse selection in insurance is a bad thing. This present blog gives the counter-argument from my book Loss Coverage: Why Insurance Works Better with Some Adverse Selection. In essence, the counter-argument relies only on simple arithmetic, and can be illustrated by a toy example. Think of a […]

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  • 25 May 2017
    Guy Thomas

    Insurance and adverse selection: orthodoxy

    Guy Thomas explores why adverse selection in insurance is usually seen as a bad thing in the first of two blog posts based on his new book Loss Coverage.

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