Previous Recipients of Gold Medals 1892 the Rt Hon Charles Booth
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School of Social Sciences Economics Division University of Southampton Southampton SO17 1BJ, UK Discussion Papers in Economics and Econometrics Mathematics in the Statistical Society 1883-1933 John Aldrich No. 0919 This paper is available on our website http://www.southampton.ac.uk/socsci/economics/research/papers ISSN 0966-4246 Mathematics in the Statistical Society 1883-1933* John Aldrich Economics Division School of Social Sciences University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract This paper considers the place of mathematical methods based on probability in the work of the London (later Royal) Statistical Society in the half-century 1883-1933. The end-points are chosen because mathematical work started to appear regularly in 1883 and 1933 saw the formation of the Industrial and Agricultural Research Section– to promote these particular applications was to encourage mathematical methods. In the period three movements are distinguished, associated with major figures in the history of mathematical statistics–F. Y. Edgeworth, Karl Pearson and R. A. Fisher. The first two movements were based on the conviction that the use of mathematical methods could transform the way the Society did its traditional work in economic/social statistics while the third movement was associated with an enlargement in the scope of statistics. The study tries to synthesise research based on the Society’s archives with research on the wider history of statistics. Key names : Arthur Bowley, F. Y. Edgeworth, R. A. Fisher, Egon Pearson, Karl Pearson, Ernest Snow, John Wishart, G. Udny Yule. Keywords : History of Statistics, Royal Statistical Society, mathematical methods. -
Royal Statistical Scandal
Royal Statistical Scandal False and misleading claims by the Royal Statistical Society Including on human poverty and UN global goals Documentary evidence Matt Berkley Draft 27 June 2019 1 "The Code also requires us to be competent. ... We must also know our limits and not go beyond what we know.... John Pullinger RSS President" https://www.statslife.org.uk/news/3338-rss-publishes-revised-code-of- conduct "If the Royal Statistical Society cannot provide reasonable evidence on inflation faced by poor people, changing needs, assets or debts from 2008 to 2018, I propose that it retract the honour and that the President makes a statement while he holds office." Matt Berkley 27 Dec 2018 2 "a recent World Bank study showed that nearly half of low-and middle- income countries had insufficient data to monitor poverty rates (2002- 2011)." Royal Statistical Society news item 2015 1 "Max Roser from Oxford points out that newspapers could have legitimately run the headline ' Number of people in extreme poverty fell by 137,000 since yesterday' every single day for the past 25 years... Careless statistical reporting could cost lives." President of the Royal Statistical Society Lecture to the Independent Press Standards Organisation April 2018 2 1 https://www.statslife.org.uk/news/2495-global-partnership-for- sustainable-development-data-launches-at-un-summit 2 https://www.statslife.org.uk/features/3790-risk-statistics-and-the-media 3 "Mistaken or malicious misinformation can change your world... When the government is wrong about you it will hurt you too but you may never know how. -
AMSTATNEWS the Membership Magazine of the American Statistical Association •
May 2021 • Issue #527 AMSTATNEWS The Membership Magazine of the American Statistical Association • http://magazine.amstat.org 2021 COPSS AWARD WINNERS ALSO: ASA, International Community Continue to Decry Georgiou Persecution Birth of an ASA Outreach Group: The Origins of JEDI AMSTATNEWS MAY 2021 • ISSUE #527 Executive Director Ron Wasserstein: [email protected] Associate Executive Director and Director of Operations Stephen Porzio: [email protected] features Senior Advisor for Statistics Communication and Media Innovation 3 President’s Corner Regina Nuzzo: [email protected] 5 ASA, International Community Continue to Decry Director of Science Policy Georgiou Persecution Steve Pierson: [email protected] Director of Strategic Initiatives and Outreach 8 What a Year! Practical Significance Celebrates Resilient Donna LaLonde: [email protected] Class of 2021 Director of Education 9 Significance Launches Data Economy Series with April Issue Rebecca Nichols: [email protected] 10 CHANCE Highlights: Spring Issue Features Economic Managing Editor Impact of COVID-19, Kullback’s Career, Sharing Data Megan Murphy: [email protected] 11 Forget March Madness! Students Test Probability Skills Editor and Content Strategist with March Randomness Val Nirala: [email protected] 12 My ASA Story: James Cochran Advertising Manager Joyce Narine: [email protected] 14 StatFest Back for 21st Year in 2021 Production Coordinators/Graphic Designers 15 Birth of an ASA Outreach Group: The Origins of JEDI Olivia Brown: [email protected] Megan Ruyle: [email protected] 18 2021 COPSS Award Winners Contributing Staff Members 23 A Story of COVID-19, Mentoring, and West Virginia Kim Gilliam Amstat News welcomes news items and letters from readers on matters of interest to the association and the profession. -
Higher-Order Asymptotics
Higher-Order Asymptotics Todd Kuffner Washington University in St. Louis WHOA-PSI 2016 1 / 113 First- and Higher-Order Asymptotics Classical Asymptotics in Statistics: available sample size n ! 1 First-Order Asymptotic Theory: asymptotic statements that are correct to order O(n−1=2) Higher-Order Asymptotics: refinements to first-order results 1st order 2nd order 3rd order kth order error O(n−1=2) O(n−1) O(n−3=2) O(n−k=2) or or or or o(1) o(n−1=2) o(n−1) o(n−(k−1)=2) Why would anyone care? deeper understanding more accurate inference compare different approaches (which agree to first order) 2 / 113 Points of Emphasis Convergence pointwise or uniform? Error absolute or relative? Deviation region moderate or large? 3 / 113 Common Goals Refinements for better small-sample performance Example Edgeworth expansion (absolute error) Example Barndorff-Nielsen’s R∗ Accurate Approximation Example saddlepoint methods (relative error) Example Laplace approximation Comparative Asymptotics Example probability matching priors Example conditional vs. unconditional frequentist inference Example comparing analytic and bootstrap procedures Deeper Understanding Example sources of inaccuracy in first-order theory Example nuisance parameter effects 4 / 113 Is this relevant for high-dimensional statistical models? The Classical asymptotic regime is when the parameter dimension p is fixed and the available sample size n ! 1. What if p < n or p is close to n? 1. Find a meaningful non-asymptotic analysis of the statistical procedure which works for any n or p (concentration inequalities) 2. Allow both n ! 1 and p ! 1. 5 / 113 Some First-Order Theory Univariate (classical) CLT: Assume X1;X2;::: are i.i.d. -
Bayesian Inference for Heterogeneous Event Counts
Bayesian Inference for Heterogeneous Event Counts ANDREW D. MARTIN Washington University This article presents an integrated set of Bayesian tools one can use to model hetero- geneous event counts. While models for event count cross sections are now widely used, little has been written about how to model counts when contextual factors introduce heterogeneity. The author begins with a discussion of Bayesian cross-sectional count models and discusses an alternative model for counts with overdispersion. To illustrate the Bayesian framework, the author fits the model to the number of women’s rights cosponsorships for each member of the 83rd to 102nd House of Representatives. The model is generalized to allow for contextual heterogeneity. The hierarchical model allows one to explicitly model contextual factors and test alternative contextual explana- tions, even with a small number of contextual units. The author compares the estimates from this model with traditional approaches and discusses software one can use to easily implement these Bayesian models with little start-up cost. Keywords: event count; Markov chain Monte Carlo; hierarchical Bayes; multilevel models; BUGS INTRODUCTION Heterogeneity is what makes society and, for that matter, statistics interesting. However, until recently, little attention has been paidto modeling count data observed in heterogeneous clusters (a notable exception is Sampson, Raudenbush, and Earls 1997). Explanations AUTHOR’S NOTE: This research is supported by the National Science Foundation Law and Social Sciences and Methodology, Measurement, and Statistics Sections, Grant SES-0135855 to Washing- ton University. I would like to thank Dave Peterson, Kevin Quinn, and Kyle Saunders for their helpful comments. I am particularly indebted to Christina Wolbrecht for sharing her valuable data set with me. -
National Academy Elects IMS Fellows Have You Voted Yet?
Volume 38 • Issue 5 IMS Bulletin June 2009 National Academy elects IMS Fellows CONTENTS The United States National Academy of Sciences has elected 72 new members and 1 National Academy elects 18 foreign associates from 15 countries in recognition of their distinguished and Raftery, Wong continuing achievements in original research. Among those elected are two IMS Adrian Raftery 2 Members’ News: Jianqing Fellows: , Blumstein-Jordan Professor of Statistics and Sociology, Center Fan; SIAM Fellows for Statistics and the Social Sciences, University of Washington, Seattle, and Wing Hung Wong, Professor 3 Laha Award recipients of Statistics and Professor of Health Research and Policy, 4 COPSS Fisher Lecturer: Department of Statistics, Stanford University, California. Noel Cressie The election was held April 28, during the business 5 Members’ Discoveries: session of the 146th annual meeting of the Academy. Nicolai Meinshausen Those elected bring the total number of active members 6 Medallion Lecture: Tony Cai to 2,150. Foreign associates are non-voting members of the Academy, with citizenship outside the United States. Meeting report: SSP Above: Adrian Raftery 7 This year’s election brings the total number of foreign 8 New IMS Fellows Below: Wing H. Wong associates to 404. The National Academy of Sciences is a private 10 Obituaries: Keith Worsley; I.J. Good organization of scientists and engineers dedicated to the furtherance of science and its use for general welfare. 12-3 JSM program highlights; It was established in 1863 by a congressional act of IMS sessions at JSM incorporation signed by Abraham Lincoln that calls on 14-5 JSM tours; More things to the Academy to act as an official adviser to the federal do in DC government, upon request, in any matter of science or 16 Accepting rejections technology. -
JSM 2017 in Baltimore the 2017 Joint Statistical Meetings in Baltimore, Maryland, Which Included the CONTENTS IMS Annual Meeting, Took Place from July 29 to August 3
Volume 46 • Issue 6 IMS Bulletin September 2017 JSM 2017 in Baltimore The 2017 Joint Statistical Meetings in Baltimore, Maryland, which included the CONTENTS IMS Annual Meeting, took place from July 29 to August 3. There were over 6,000 1 JSM round-up participants from 52 countries, and more than 600 sessions. Among the IMS program highlights were the three Wald Lectures given by Emmanuel Candès, and the Blackwell 2–3 Members’ News: ASA Fellows; ICM speakers; David Allison; Lecture by Martin Wainwright—Xiao-Li Meng writes about how inspirational these Mike Cohen; David Cox lectures (among others) were, on page 10. There were also five Medallion lectures, from Edoardo Airoldi, Emery Brown, Subhashis Ghoshal, Mark Girolami and Judith 4 COPSS Awards winners and nominations Rousseau. Next year’s IMS lectures 6 JSM photos At the IMS Presidential Address and Awards session (you can read Jon Wellner’s 8 Anirban’s Angle: The State of address in the next issue), the IMS lecturers for 2018 were announced. The Wald the World, in a few lines lecturer will be Luc Devroye, the Le Cam lecturer will be Ruth Williams, the Neyman Peter Bühlmann Yuval Peres 10 Obituary: Joseph Hilbe lecture will be given by , and the Schramm lecture by . The Medallion lecturers are: Jean Bertoin, Anthony Davison, Anna De Masi, Svante Student Puzzle Corner; 11 Janson, Davar Khoshnevisan, Thomas Mikosch, Sonia Petrone, Richard Samworth Loève Prize and Ming Yuan. 12 XL-Files: The IMS Style— Next year’s JSM invited sessions Inspirational, Mathematical If you’re feeling inspired by what you heard at JSM, you can help to create the 2018 and Statistical invited program for the meeting in Vancouver (July 28–August 2, 2018). -
NEWSLETTER Issue: 491 - November 2020
i “NLMS_491” — 2020/10/28 — 11:56 — page 1 — #1 i i i NEWSLETTER Issue: 491 - November 2020 COXETER THE ROYAL INSTITUTION FRIEZES AND PROBABILIST’S CHRISTMAS GEOMETRY URN LECTURER i i i i i “NLMS_491” — 2020/10/28 — 11:56 — page 2 — #2 i i i EDITOR-IN-CHIEF COPYRIGHT NOTICE Eleanor Lingham (Sheeld Hallam University) News items and notices in the Newsletter may [email protected] be freely used elsewhere unless otherwise stated, although attribution is requested when reproducing whole articles. Contributions to EDITORIAL BOARD the Newsletter are made under a non-exclusive June Barrow-Green (Open University) licence; please contact the author or David Chillingworth (University of Southampton) photographer for the rights to reproduce. Jessica Enright (University of Glasgow) The LMS cannot accept responsibility for the Jonathan Fraser (University of St Andrews) accuracy of information in the Newsletter. Views Jelena Grbic´ (University of Southampton) expressed do not necessarily represent the Cathy Hobbs (UWE) views or policy of the Editorial Team or London Christopher Hollings (Oxford) Mathematical Society. Stephen Huggett Adam Johansen (University of Warwick) ISSN: 2516-3841 (Print) Susan Oakes (London Mathematical Society) ISSN: 2516-385X (Online) Andrew Wade (Durham University) DOI: 10.1112/NLMS Mike Whittaker (University of Glasgow) Early Career Content Editor: Jelena Grbic´ NEWSLETTER WEBSITE News Editor: Susan Oakes Reviews Editor: Christopher Hollings The Newsletter is freely available electronically at lms.ac.uk/publications/lms-newsletter. CORRESPONDENTS AND STAFF MEMBERSHIP LMS/EMS Correspondent: David Chillingworth Joining the LMS is a straightforward process. For Policy Digest: John Johnston membership details see lms.ac.uk/membership. -
Agenda and Minutes of the UK Statistics Authority Meeting on 6
UK STATISTICS AUTHORITY Minutes Thursday, 6 June 2013 Boardroom, Titchfield Present UK Statistics Authority Sir Andrew Dilnot (Chair) Professor David Rhind Professor Sir Adrian Smith Mr Richard Alldritt Mr Partha Dasgupta Ms Carolyn Fairbairn Dame Moira Gibb Professor David Hand Dr David Levy Ms Jil Matheson Mr Glen Watson Secretariat Mr Robert Bumpstead Mr Joe Cuddeford Apologies Dr Colette Bowe Other attendees Mr Peter Benton, Mr Alistair Calder and Mr Ian Cope (for item 7) Minutes 1. Apologies 1.1 Apologies were received from Dr Bowe. 2. Declarations of interest 2.1 There were no declarations of interest. 3. Minutes, matters arising from the previous meetings 3.1 The minutes of the previous meeting held on 9 May 2013 were agreed as a true and fair account. 3.2 It was confirmed that a paper from ONS about migration statistics would be considered at the July Authority Board meeting. 4. Authority Chair’s Report 4.1 The Chair had recently attended a meeting of the Cabinet’s Ministerial Committee on Home Affairs to discuss the future provision of population statistics for England and Wales. 4.2 The Chair would be meeting with the Work and Pensions Select Committee on 10 June to discuss official statistics in the Department for Work and Pensions. 4.3 The Chair had written to the Secretary of State for Work and Pensions, Iain Duncan Smith MP, regarding statistics about the benefit cap, and the Chairman of the Conservative Party, Grant Shapps MP, regarding statistics about the Employment and Support Allowance. 5. Reports from Authority Committee Chairs Assessment Committee 5.1 Professor Rhind reported on the meeting of the Assessment Committee held on 16 May. -
Gladstone and the Bank of England: a Study in Mid-Victorian Finance, 1833-1866
GLADSTONE AND THE BANK OF ENGLAND: A STUDY IN MID-VICTORIAN FINANCE, 1833-1866 Patricia Caernarv en-Smith, B.A. Thesis Prepared for the Degree of MASTER OF ARTS UNIVERSITY OF NORTH TEXAS May 2007 APPROVED: Denis Paz, Major Professor Adrian Lewis, Committee Member and Chair of the Department of History Laura Stern, Committee Member Sandra L. Terrell, Dean of the Robert B. Toulouse School of Graduate Studies Caernarven-Smith, Patricia. Gladstone and the Bank of England: A Study in Mid- Victorian Finance, 1833-1866. Master of Arts (History), May 2007, 378 pp., 11 tables, bibliography, 275 titles. The topic of this thesis is the confrontations between William Gladstone and the Bank of England. These confrontations have remained a mystery to authors who noted them, but have generally been ignored by others. This thesis demonstrates that Gladstone’s measures taken against the Bank were reasonable, intelligent, and important for the development of nineteenth-century British government finance. To accomplish this task, this thesis refutes the opinions of three twentieth-century authors who have claimed that many of Gladstone’s measures, as well as his reading, were irrational, ridiculous, and impolitic. My primary sources include the Gladstone Diaries, with special attention to a little-used source, Volume 14, the indexes to the Diaries. The day-to-day Diaries and the indexes show how much Gladstone read about financial matters, and suggest that his actions were based to a large extent upon his reading. In addition, I have used Hansard’s Parliamentary Debates and nineteenth-century periodicals and books on banking and finance to understand the political and economic debates of the time. -
Memorial to Sir Harold Jeffreys 1891-1989 JOHN A
Memorial to Sir Harold Jeffreys 1891-1989 JOHN A. HUDSON and ALAN G. SMITH University of Cambridge, Cambridge, England Harold Jeffreys was one of this century’s greatest applied mathematicians, using mathematics as a means of under standing the physical world. Principally he was a geo physicist, although statisticians may feel that his greatest contribution was to the theory of probability. However, his interest in the latter subject stemmed from his realization of the need for a clear statistical method of analysis of data— at that time, travel-time readings from seismological stations across the world. He also made contributions to astronomy, fluid dynamics, meteorology, botany, psychol ogy, and photography. Perhaps one can identify Jeffreys’s principal interests from three major books that he wrote. His mathematical skills are displayed in Methods of Mathematical Physics, which he wrote with his wife Bertha Swirles Jeffreys and which was first published in 1946 and went through three editions. His Theory o f Probability, published in 1939 and also running to three editions, espoused Bayesian statistics, which were very unfashionable at the time but which have been taken up since by others and shown to be extremely powerful for the analysis of data and, in particular, image enhancement. However, the book for which he is probably best known is The Earth, Its Origin, History and Physical Consti tution, a broad-ranging account based on observations analyzed with care, using mathematics as a tool. Jeffreys’s scientific method (now known as Inverse Theory) was a logical process, clearly stated in another of his books, Scientific Inference. -
A Parsimonious Tour of Bayesian Model Uncertainty
A Parsimonious Tour of Bayesian Model Uncertainty Pierre-Alexandre Mattei Université Côte d’Azur Inria, Maasai project-team Laboratoire J.A. Dieudonné, UMR CNRS 7351 e-mail: [email protected] Abstract: Modern statistical software and machine learning libraries are enabling semi-automated statistical inference. Within this context, it appears eas- ier and easier to try and fit many models to the data at hand, thereby reversing the Fisherian way of conducting science by collecting data after the scientific hypothesis (and hence the model) has been determined. The renewed goal of the statistician becomes to help the practitioner choose within such large and heterogeneous families of models, a task known as model selection. The Bayesian paradigm offers a systematized way of as- sessing this problem. This approach, launched by Harold Jeffreys in his 1935 book Theory of Probability, has witnessed a remarkable evolution in the last decades, that has brought about several new theoretical and methodological advances. Some of these recent developments are the focus of this survey, which tries to present a unifying perspective on work carried out by different communities. In particular, we focus on non-asymptotic out-of-sample performance of Bayesian model selection and averaging tech- niques, and draw connections with penalized maximum likelihood. We also describe recent extensions to wider classes of probabilistic frameworks in- cluding high-dimensional, unidentifiable, or likelihood-free models. Contents 1 Introduction: collecting data, fitting many models . .2 2 A brief history of Bayesian model uncertainty . .2 3 The foundations of Bayesian model uncertainty . .3 3.1 Handling model uncertainty with Bayes’s theorem .