March event: Careers in Statistics

All members, especially young statisticians, are welcome to the following event on careers in statistics taking place on Wednesday 26th March 2014, starting from 1pm.

This *free* event is designed to broaden the horizons of career-young statisticians through showcasing the wide range of different statistical careers that are available. Statistics covers fields as diverse as medicine, finance, industry, environment, government and academia. There will be a range of talks from these areas with invaluable networking opportunities.

Speakers are confirmed from Phastar, AstraZeneca, Sparx, NowGen, Department of Work and Pensions, and other companies based in northern England.

The event is intended for anyone about to embark on, or at the beginning of, their statistical career, so whether you have already begun to specialise in a particular area of statistics or are still studying, the day is sure to be of great value.

The event is *free of charge* but we do ask participants to register at

Venue: Alan Turing Building, University of Manchester.
This is building is #46 on the campus map where you can also find travel information.:


1:00 – 1:30  Arrival

1:30 – 3:00  Session 1 – including talks from Royal statistical society, an environmental statistician, department of work and pensions, and a Professor of Medical Statistics.

3:00 – 3:30 Coffee and Refreshments

3:30 – 5:00 Session 2 – including talks from Astrazeneca, Phastar, NowGen and a local clinical trials unit

5:00 Wine reception and networking

This is jointly organised by University of Manchester School of Mathematics, and the Royal Statistical Society (Young Statisticians’ Section and Manchester Local Group).

Please direct any queries about the event to Matthew Sperrin:

We look forward to seeing you in Manchester!

Organising Committee:
Peter Foster
Christiana Charalambous
Mark Pilling
Elizabeth Boggis
Matthew Sperrin

December seminar: Assessing Disclosure Risk in Sample Microdata

Date: Wednesday 11th December 2013

Time: 16:00-17:00 (tea/coffee and mince pies available from 15.30)

Venue: Room G207, Alan Turing Building, The University of Manchester, Manchester

Building 46 on the campus map:

Assessing Disclosure Risk in Sample Microdata

Professor Natalie Shlomo
Professor of Social Statistics, The Cathie Marsh Centre for Census and Survey Research, University of Manchester

Disclosure risk occurs when there is a high probability that an intruder can identify an individual in released sample microdata and confidential information may be revealed.  For most social surveys, the population from which the sample is drawn is generally not known or only partially known through marginal distributions. The identification is made possible through the use of a key, which is a combination of indirectly identifying variables, such as age, sex and place of residence. Disclosure risk measures are based on the notion of population uniqueness in the key. In order to quantify the disclosure risk, probabilistic models are defined based on distributional assumptions about the population counts inferred from the observed sample counts. The parameters for the distribution are estimated through log-linear models.  The probabilistic framework is expanded to cover the case of misclassification on the key variables, either arising from the  survey process or as a  result of perturbative disclosure control techniques that may have been applied to the data. The methods are demonstrated on real data drawn from extracts of the 2001 United Kingdom Census.

This is joint work with Prof. Chris Skinner of the London School of Economics and Political Science.