Performance Indicators: Good, Bad, and Ugly
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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). -
You May Be (Stuck) Here! and Here Are Some Potential Reasons Why
You may be (stuck) here! And here are some potential reasons why. As published in Benchmarks RSS Matters, May 2015 http://web3.unt.edu/benchmarks/issues/2015/05/rss-matters Jon Starkweather, PhD 1 Jon Starkweather, PhD [email protected] Consultant Research and Statistical Support http://www.unt.edu http://www.unt.edu/rss RSS hosts a number of “Short Courses”. A list of them is available at: http://www.unt.edu/rss/Instructional.htm Those interested in learning more about R, or how to use it, can find information here: http://www.unt.edu/rss/class/Jon/R_SC 2 You may be (stuck) here! And here are some potential reasons why. I often read R-bloggers (Galili, 2015) to see new and exciting things users are doing in the wonderful world of R. Recently I came across Norm Matloff’s (2014) blog post with the title “Why are we still teaching t-tests?” To be honest, many RSS personnel have echoed Norm’s sentiments over the years. There do seem to be some fields which are perpetually stuck in decades long past — in terms of the statistical methods they teach and use. Reading Norm’s post got me thinking it might be good to offer some explanations, or at least opinions, on why some fields tend to be stubbornly behind the analytic times. This month’s article will offer some of my own thoughts on the matter. I offer these opinions having been academically raised in one such Rip Van Winkle (Washington, 1819) field and subsequently realized how much of what I was taught has very little practical utility with real world research problems and data. -
Statistics Making an Impact
John Pullinger J. R. Statist. Soc. A (2013) 176, Part 4, pp. 819–839 Statistics making an impact John Pullinger House of Commons Library, London, UK [The address of the President, delivered to The Royal Statistical Society on Wednesday, June 26th, 2013] Summary. Statistics provides a special kind of understanding that enables well-informed deci- sions. As citizens and consumers we are faced with an array of choices. Statistics can help us to choose well. Our statistical brains need to be nurtured: we can all learn and practise some simple rules of statistical thinking. To understand how statistics can play a bigger part in our lives today we can draw inspiration from the founders of the Royal Statistical Society. Although in today’s world the information landscape is confused, there is an opportunity for statistics that is there to be seized.This calls for us to celebrate the discipline of statistics, to show confidence in our profession, to use statistics in the public interest and to champion statistical education. The Royal Statistical Society has a vital role to play. Keywords: Chartered Statistician; Citizenship; Economic growth; Evidence; ‘getstats’; Justice; Open data; Public good; The state; Wise choices 1. Introduction Dictionaries trace the source of the word statistics from the Latin ‘status’, the state, to the Italian ‘statista’, one skilled in statecraft, and on to the German ‘Statistik’, the science dealing with data about the condition of a state or community. The Oxford English Dictionary brings ‘statistics’ into English in 1787. Florence Nightingale held that ‘the thoughts and purpose of the Deity are only to be discovered by the statistical study of natural phenomena:::the application of the results of such study [is] the religious duty of man’ (Pearson, 1924). -
ISI99 Daily Bulletin 4
ISI99 Daily Bulletin 4 Thursday 12 August, 1999 Contents First day • ISI Service Awards 2 • Jan Tinbergen Awards 1999 2 • Changes in the programme 3 • Correction 3 • Statistical Education 3 • Making Statistics Come Alive 4 • Behind the scenes and in the frontline, part 3 5 IASS - International Association • Many questions were answered at the Information Desk. of Survey Statisticians 6 • Everyday elegance anyone can afford 6 • Golden era of Finnish art 8 • Ateneum, the ”House for the Arts” 9 • Kiasma, the museum of contemporary art 9 • The spirit of the bottle 10 • Harvest in the Market Square 11 • Kuka hän on? 12 • For people on the move 12 Webmasters Markku (left) and Samppa mastering the Web. ISI99 / Daily Bulletin / Thursday, August 12 / 4 1 ISI Service Awards From time to time, the President awards ISI Service Medals to Adolphe Quetelet (Belgium) persons whose outstanding activities were of particular Henri Willem Methorst (The Netherlands) significance for the Institute’s activities. The Service Medals are Franz von Neumann–Spallart (Austria–Hungary) named after three great statisticians who were instrumental in The ISI Executive Committee considers the following persons furthering international statistical co-operation: as deserving candidates for an ISI Service Medal, to be awarded during the August 13 ISI General Assembly meeting in Helsinki: Adolphe Quetelet Medal David Cox (United Kingdom) Ilkka Mellin (Finland) Mario Palma Rojo (Mexico) Timo Relander (Finland) Vijayan N. Nair (Malaysia) Zoltan Kenessey (in memorial -USA) Willem de Vries (Netherlands) Henri Willem Methorst Medal Constance van Eeden (The Netherlands) Agnes Herzberg (Canada) Raija Lofgren (Finland) Joop Mijnheer (The Netherlands) Jozef L.M. -
Error and Inference: an Outsider Stand on a Frequentist Philosophy
ERROR AND INFERENCE: AN OUTSIDER STAND ON A FREQUENTIST PHILOSOPHY CHRISTIAN P. ROBERT UNIVERSITE´ PARIS-DAUPHINE CEREMADE, IUF, AND CREST, 75775 PARIS CEDEX 16, FRANCE [email protected] Abstract. This note is an extended review of the book Error and Inference, edited by Deborah Mayo and Aris Spanos, about their frequentist and philosophical perspective on testing of hypothesis and on the criticisms of alternatives like the Bayesian approach. 1. Introduction. “The philosophy of science offer valuable tools for understanding and ad- vancing solutions to the problems of evidence and inference in practice”— D. Mayo and A. Spanos, p.xiv, Error and Inference, 2010 This philosophy book, Error and Inference, whose subtitle is “Recent exchanges on experimental reasoning, reliability, and the objectivity and rationality of Science”, includes contributions by P. Achinstein, A. Chalmers, D. Cox, C. Glymour, L. Laudan, A. Musgrave, and J. Worrall, and by both editors, D. Mayo and A. Spanos. It offers reflections on the nature of testing and the defence of the “Error-Statistical philosophy”, proposed by Mayo (1996). Error and Inference is the edited continuation of a conference held at Virginia Tech in 2006, ERROR 06. Given my layman interest in the philosophy of Science, I find that the book reads rather well, despite my missing references in the field. (Paradoxically, the sections I found the hardest to follow were those most centred on Statistics.) The volume is very carefully edited and thus much more than a collection of papers, thanks to the dedications of the editors. In particular, Deborah Mayo added her comments at the end of the chapters of all contributors (but her own’s and Aris Spanos’). -
Survey Methodology
Catalogue no. 12-001-XIE Survey Methodology December 2007 Statistics Statistique Canada Canada How to obtain more information Specifi c inquiries about this product and related statistics or services should be directed to: Business Survey Methods Division, Statistics Canada, Ottawa, Ontario, K1A 0T6 (telephone: 1-800-263-1136). For information on the wide range of data available from Statistics Canada, you can contact us by calling one of our toll-free numbers. You can also contact us by e-mail or by visiting our website at www.statcan.ca. National inquiries line 1-800-263-1136 National telecommunications device for the hearing impaired 1-800-363-7629 Depository Services Program inquiries 1-800-700-1033 Fax line for Depository Services Program 1-800-889-9734 E-mail inquiries [email protected] Website www.statcan.ca Accessing and ordering information This product, catalogue no. 12-001-XIE, is available for free in electronic format. To obtain a single issue, visit our website at www.statcan.ca and select Publications. This product, catalogue no. 12-001-XPB, is also available as a standard printed publication at a price of CAN$30.00 per issue and CAN$58.00 for a one-year subscription. The following additional shipping charges apply for delivery outside Canada: Single issue Annual subscription United States CAN$6.00 CAN$12.00 Other countries CAN$10.00 CAN$20.00 All prices exclude sales taxes. The printed version of this publication can be ordered by • Phone (Canada and United States) 1-800-267-6677 • Fax (Canada and United States) 1-877-287-4369 • E-mail [email protected] • Mail Statistics Canada Finance Division R.H. -
Probability, Analysis and Number Theory
Probability, Analysis and Number Theory. Papers in Honour of N. H. Bingham (ed. C. M. Goldie and A. Mijatovi´c), Advances in Applied Probability Special Volume 48A (2016), 1-14. PROBABILITY UNFOLDING, 1965-2015 N. H. BINGHAM Abstract. We give a personal (and we hope, not too idiosyncratic) view of how our subject of Probability Theory has developed during the last half-century, and the author in tandem with it. 1. Introduction. One of the nice things about Probability Theory is that it is still a young subject. Of course it has ancient roots in the real world, as chance is all around us, and draws on the older fields of Analysis on the one hand and Statistics on the other. We take the conventional view that the modern era begins in 1933 with Kolmogorov's path-breaking Grundbegriffe, and agree with Williams' view of probability pre-Kolmogorov as `a shambles' (Williams (2001), 23)1. The first third of the last century was an interesting transitional period, as Measure Theory, the natural machinery with which to do Proba- bility, already existed. For my thoughts on this period, see [72]2, [104]; for the origins of the Grundbegriffe, see e.g. Shafer & Vovk (2006). Regarding the history of mathematics in general, we have among a wealth of sources the two collections edited by Pier (1994, 2000), covering 1900- 50 and 1950-2000. These contain, by Doob and Meyer respectively (Doob (1994), Meyer (2000)), fine accounts of the development of probability; Meyer (2000) ends with his 12-page selection of a chronological list of key publica- tions during the century. -
Royal Statistical Society Duties of Council Members Council Is The
Royal Statistical Society Duties of Council members Council is the governing body of the Society and its members are elected by the Fellowship. Council sets the long term strategy, the business plan and oversight of all the RSS’s many activities including financial matters. Council members are elected to serve for a maximum term of office of 4 years. Members attend the RSS Council which meets 5 times a year at Errol Street in London to conduct its formal meetings. These meetings are from 11am-4pm and are in: January, April, July, October and December. New members are invited to attend the December meeting prior to the session for which they have been elected. Members usually become involved, as a Council representative, in other areas of the RSS for example, by serving on a standing committee, section committee, working party or theme. Some members, who already serve the Society in another capacity, may not have the time to take on a further role but usually many do. Involvement in other areas does not necessarily require attendance at meetings. Each of the 12 themes (which support the delivery and development of the RSS’s activities) are developing support or consultation groups which members are encouraged to join and often this is conducted by email. Council members are not only trustees of the Society but are ambassadors for furthering the Society’s aims. Members of Council are sometimes asked to represent the President at formal functions or other events and all Council members are invited to get involved in specific activities such as: • Joining the media contacts list; • Promoting membership of the Society to colleagues; • Talking to students or school children about statistics. -
International Prize in Statistics Awarded to Sir David Cox for Survival Analysis Model Applied in Medicine, Science, and Engineering
International Prize in Statistics Awarded to Sir David Cox for Survival Analysis Model Applied in Medicine, Science, and Engineering EMBARGOED until October 19, 2016, at 9 p.m. ET ALEXANDRIA, VA (October 18, 2016) – Prominent British statistician Sir David Cox has been named the inaugural recipient of the International Prize in Statistics. Like the acclaimed Fields Medal, Abel Prize, Turing Award and Nobel Prize, the International Prize in Statistics is considered the highest honor in its field. It will be bestowed every other year to an individual or team for major achievements using statistics to advance science, technology and human welfare. Cox is a giant in the field of statistics, but the International Prize in Statistics Foundation is recognizing him specifically for his 1972 paper in which he developed the proportional hazards model that today bears his name. The Cox Model is widely used in the analysis of survival data and enables researchers to more easily identify the risks of specific factors for mortality or other survival outcomes among groups of patients with disparate characteristics. From disease risk assessment and treatment evaluation to product liability, school dropout, reincarceration and AIDS surveillance systems, the Cox Model has been applied essentially in all fields of science, as well as in engineering. “Professor Cox changed how we analyze and understand the effect of natural or human- induced risk factors on survival outcomes, paving the way for powerful scientific inquiry and discoveries that have impacted -
Curriculum Vitae
Curriculum Vitae Nancy Margaret Reid O.C. April, 2021 BIOGRAPHICAL INFORMATION Personal University Address: Department of Statistical Sciences University of Toronto 700 University Avenue 9th floor Toronto, Ontario M5S 1X6 Telephone: (416) 978-5046 Degrees 1974 B.Math University of Waterloo 1976 M.Sc. University of British Columbia 1979 Ph.D. Stanford University Thesis: “Influence functions for censored data” Supervisor: R.G. Miller, Jr. 2015 D.Math. (Honoris Causa) University of Waterloo Employment 1-3/2020 Visiting Professor SMRI University of Sydney 1-3/2020 Visiting Professor Monash University Melbourne 10-11/2012 Visiting Professor Statistical Science University College, London 2007-2021 Canada Research Chair Statistics University of Toronto 2003- University Professor Statistics University of Toronto 1988- Professor Statistics University of Toronto 2002-2003 Visiting Professor Mathematics EPF, Lausanne 1997-2002 Chair Statistics University of Toronto 1987- Tenured Statistics University of Toronto 1986-88 Associate Professor Statistics University of Toronto Appointed to School of Graduate Studies 1986/01-06 Visiting Associate Professor Mathematics Univ. of Texas at Austin 1985/07-12 Visiting Associate Professor Biostatistics Harvard School of Public Health 1985-86 Associate Professor Statistics Univ. of British Columbia Tenured Statistics Univ. of British Columbia 1980-85 Assistant Professor Statistics & Mathematics Univ. of British Columbia 1979-80 Nato Postdoctoral Fellow Mathematics Imperial College, London 1 Honours 2020 Inaugural -
Good, Irving John Employment Grants Degrees and Honors
CV_July_24_04 Good, Irving John Born in London, England, December 9, 1916 Employment Foreign Office, 1941-45. Worked at Bletchley Park on Ultra (both the Enigma and a Teleprinter encrypting machine the Schlüsselzusatz SZ40 and 42 which we called Tunny or Fish) as the main statistician under A. M. Turing, F. R. S., C. H. O. D. Alexander (British Chess Champion twice), and M. H. A. Newman, F. R. S., in turn. (All three were friendly bosses.) Lecturer in Mathematics and Electronic Computing, Manchester University, 1945-48. Government Communications Headquarters, U.K., 1948-59. Visiting Research Associate Professor, Princeton, 1955 (Summer). Consultant to IBM for a few weeks, 1958/59. (Information retrieval and evaluation of the Perceptron.) Admiralty Research Laboratory, 1959-62. Consultant, Communications Research Division of the Institute for Defense Analysis, 1962-64. Senior Research Fellow, Trinity College, Oxford, and Atlas Computer Laboratory, Science Research Council, Great Britain, 1964-67. Professor (research) of Statistics, Virginia Polytechnic Institute and State University since July, 1967. University Distinguished Professor since Nov. 19, 1969. Emeritus since July 1994. Adjunct Professor of the Center for the Study of Science in Society from October 19, 1983. Adjunct Professor of Philosophy from April 6, 1984. Grants A grant, Probability Estimation, from the U.S. Dept. of Health, Education and Welfare; National Institutes of Health, No. R01 Gm 19770, was funded in 1970 and was continued until July 31, 1989. (Principal Investigator.) Also involved in a grant obtained by G. Tullock and T. N. Tideman on Public Choice, NSF Project SOC 78-06180; 1977-79. Degrees and Honors Rediscovered irrational numbers at the age of 9 (independently discovered by the Pythagoreans and described by the famous G.H.Hardy as of “profound importance”: A Mathematician’s Apology, §14). -
“It Took a Global Conflict”— the Second World War and Probability in British
Keynames: M. S. Bartlett, D.G. Kendall, stochastic processes, World War II Wordcount: 17,843 words “It took a global conflict”— the Second World War and Probability in British Mathematics John Aldrich Economics Department University of Southampton Southampton SO17 1BJ UK e-mail: [email protected] Abstract In the twentieth century probability became a “respectable” branch of mathematics. This paper describes how in Britain the transformation came after the Second World War and was due largely to David Kendall and Maurice Bartlett who met and worked together in the war and afterwards worked on stochastic processes. Their interests later diverged and, while Bartlett stayed in applied probability, Kendall took an increasingly pure line. March 2020 Probability played no part in a respectable mathematics course, and it took a global conflict to change both British mathematics and D. G. Kendall. Kingman “Obituary: David George Kendall” Introduction In the twentieth century probability is said to have become a “respectable” or “bona fide” branch of mathematics, the transformation occurring at different times in different countries.1 In Britain it came after the Second World War with research on stochastic processes by Maurice Stevenson Bartlett (1910-2002; FRS 1961) and David George Kendall (1918-2007; FRS 1964).2 They also contributed as teachers, especially Kendall who was the “effective beginning of the probability tradition in this country”—his pupils and his pupils’ pupils are “everywhere” reported Bingham (1996: 185). Bartlett and Kendall had full careers—extending beyond retirement in 1975 and ‘85— but I concentrate on the years of setting-up, 1940-55.