Work Of Statisticians Research Articles

Conscription Lists, Military Forces, and Demography in Hellenistic Boiotia

ABSTRACT: This article presents a new attempt to estimate the size of the army and the population of Boiotia in the Hellenistic period. The calculation is based on an important type of epigraphic evidence in the region: conscription lists from the various cities of the Boiotian Confederacy, following a method initiated by Beloch. Confidence intervals are provided to estimate the age class of 20 in each city as well as whole districts where reliable data are available, and the population model is subsequently drawn from the work of contemporary statisticians. We reach a military potential of 11,000–14,500 men aged 20–49. This equates to a citizen population (including women and children) of 59,000–78,000 and to a total population of 75,000–115,000.

“Covid has Reminded us that Independent Science is Really Important. And Statistics is Part of that” A Conversation with Steve MacFeely

Abstract Steve MacFeely is director of data and analytics at the World Health Organization, a post he took up in July 2021, during the second year of the coronavirus crisis. In this interview – part of a series highlighting the work of statisticians throughout the pandemic – he discusses the difficulties of measuring the direct and indirect effects of Covid, disruptions and innovations within national statistical systems, and his hopes – and fears – for the future. By Brian Tarran

Foundations of Contemporary Economics: Harold Hotelling on Location and Exhaustible Resources

Harold Hotelling is an influential statistician working in the field of economic theory at the beginning of the 20th century. His contributions to economics are trailblazing and open new topics for economic and business analysis. His best-known work is his solution to the problem of exhaustible resources. He also triggered the exploration of spatial economics and the analysis of product differentiation through his solution of the optimal location of producers in a duopoly. Less known, but important, are his contributions to the development of modern neoclassical microeconomic theory. Hotelling is also one of the scientists who initiated the turn towards mathematical economics in the 1950s. In this paper we provide an introduction of his groundbreaking work on economic theory.

PAINT-BY-NUMBER OR PICASSO? A GROUNDED THEORY PHENOMENOGRAPHICAL STUDY OF STUDENTS’ CONCEPTIONS OF STATISTICS

Statistics students’ conceptions of the work of statisticians and the discipline of statistics may play an important role in the topics to which they attend and their interest in pursuing further study. To learn about students’ conceptions, we collected open-ended survey responses from 44 undergraduate students who had completed introductory statistics courses. We used a grounded theory phenomenographical qualitative approach to identify several themes in students’ conceptions. In addition to the test-and-procedure conception, we offer several other themes, such as acknowledgement of variation and the role of ethical integrity. We use a metaphor of painting styles to compare to experts’ conceptions of statistics. By identifying “seeds” of what may be developed into expert conceptions, these preliminary results set possible foundations to explore trajectories that may help shape students’ conceptions of statistics.
 First published June 2020 at Statistics Education Research Journal Archives

Integrating Population Data: Challenges and Prospects

The article deals with methodological, organizational, and technological issues of integrating population data obtained from various administrative sources and corporative big data. The article proves the particular relevance of the interaction between official statistics and other governmental and corporative information systems amidst the digitization of the economy and social life and the incipient establishment of the federal population data register. The authors propose a system of interrelated aggregates, characterizing various categories of population, which differ according to criteria of citizenship, permanent residence, duration, and purposes of stay on the territory of Russia. Challenges associated with estimating these aggregates are analyzed. The article considers possibilities and legal limitations in the work of statisticians on systematizing information, rationalizing the selection and subsequent joint use of information, characterizing an individual (i.e. matching) for addressing various tasks faced by social and demographic statistics. Special attention is paid to the various options for resolving the issue of a personal code (one or more) that allow linking information on the individual from different databases. The need to ensure the transparency of the methodology used by the various participants of informational interaction is emphasized, which in turn shall pave the way for the harmonization and, where possible, the unification of such methodology. The paper demonstrates the crucial role of preliminary qualitative analysis of data from different sources and explains mechanisms for further interaction of statistical authorities with organizations, interested in this information, and social structures. Using mobile operators’ and providers’ data on the population of the city, necessary conditions for their adequate interpretation – transparent methodology, clear description of population aggregates to estimate, and assumptions used for such estimations – are characterized.

The Present State of the Study of Politics

The original outline of this article included a general overview and critique of the leading trends in the study of politics over the past 30 to 40 years. It was intended to compare the methods and results of different types of political thought-to consider in turn the historical school, the law school, researchers in the field of comparative analysis of forms of government, philosophers themselves, the approach of economists, the contribution of geographers and ethnologists, the work of statisticians, and finally to turn to psychological, sociological and biological interpretations of the political process. It would be an interesting and perhaps useful task to compare the subject and method of such thinkers as Jellinek, Gierke, Dugi, Dicey and Pound, the philosophies of Sorel and Dewey, Ritchie and Russell, Nietzsche and Tolstoy, to look at the methods of Durkheim and Simmel, Ward, Giddings and Small, Cooley and Ross, and to discuss the innovations found in the works of Wallace and Cole. It might be useful to expand the analysis to include important features of the environment in which these ideas flourished, and the many close connections between them. One could also discuss the impact of social and industrial development, class movements and class struggle or group conflicts in a broader sense, consider the impact of urbanism and industrialism, capitalism, socialism and syndicalism, militarism, pacifism, feminism, nationalism. It would be useful, perhaps, to present a critique of the methods and results described and to specifically assess the significance of logical, psychological, sociological, legal, philosophical and historical methodologies and the contribution of each of them to the study of the political. This task, however, was dropped and postponed for the next time, as it became apparent that no such review could be compressed to reasonable volumes. In order to achieve our common goal, it would seem that a different type of analysis would be more productive, aimed at reconstructing the methods of political research and obtaining more extensive results in both the theoretical and practical fields.

High price of the truth in statistics

One can expect that totalitarian and authoritarian regimes will infringe the independence of national statistical institutions. The outcome of the 1937 census in Soviet Russia disappointed Stalin, which led to the statisticians having been faced with repression. Similar cases, although very rare, can also be observed in democratic countries in the 21st century. Argentinian president's ineffective pressure to lower the inflation rate resulted in criminal charges against the person responsible for estimating the inflation rate in the Argentinian National Institute of Statistics and Censuses (INDEC). In 2018, the head of the Hellenic Statistical Authority (ELSTAT) was prosecuted for sending true macroeconomic data that revealed the causes of the crisis in Greece to the Eurostat. The article shows what price statisticians have to pay sometimes for their diligent work which accurately reflects the economic and social reality. It has to be remembered that the work of statisticians is a civil service, where ethical attitude plays an important role. The aim of the article is thus to present instances of repression of staticians by certain countries’ state authorities for showing the real picture of the social or economic situation of a given country.

Численность населения СССР в 1930-е гг.: загадки демографической истории

<span>В статье ставится задача выявить степень воздействия идеологических и политических факторов на работу советских статистиков при определении численности населения СССР в течение 12-лет, прошедших между Всесоюзными переписями 1926 и 1939 гг. В этот сложный период страна переживала форсированную индустриализацию, насильственную коллективизацию и ускоренную, хаотичную урбанизацию. В связи с чем демографическая подсистема Советского Союза претерпела принципиальные изменения. Но характер этих изменений, сдвиги в численности населения и методы, которые использовали советские статистические органы для получения важнейшей демографической информации, изучены крайне слабо. В статье показано, как сформировались два динамических ряда численности населения, составленные советскими статистиками: 1) опубликованный в открытой печати и 2) закрытый ряд, хранившийся в недрах ведомственного архива ЦУНХУ СССР. Выявлено значение регистрации рождаемости, смертности, миграций при оценках численности населения. На основании большого числа исторических документов показана сложная работа статистиков по определению численности населения в СССР 1930-х гг. Выявлены довоенные и послевоенные оценки изменений в численности населения страны.</span>

20 Years of Statistics at the National Center for Atmospheric Research

Almost every U.S.-based statistician working on problems motivated by atmospheric science is connected to the statistics program at the National Center for Atmospheric Research (NCAR). Through its permanent staff scientists, postdoctoral researchers, visitors, seminars, workshops, and published work, NCAR has made a profound impact on the community of statisticians working in the atmospheric and climate sciences. This past year saw a reorganization of statistics at NCAR. This article looks back at more than 20 years of statistics there.

Before p < 0.05 to Beyond p < 0.05: Using History to Contextualize p-Values and Significance Testing

ABSTRACT As statisticians and scientists consider a world beyond p < 0.05, it is important to not lose sight of how we got to this point. Although significance testing and p-values are often presented as prescriptive procedures, they came about through a process of refinement and extension to other disciplines. Ronald A. Fisher and his contemporaries formalized these methods in the early twentieth century and Fisher’s 1925 Statistical Methods for Research Workers brought the techniques to experimentalists in a variety of disciplines. Understanding how these methods arose, spread, and were argued over since then illuminates how p < 0.05 came to be a standard for scientific inference, the advantage it offered at the time, and how it was interpreted. This historical perspective can inform the work of statisticians today by encouraging thoughtful consideration of how their work, including proposed alternatives to the p-value, will be perceived and used by scientists. And it can engage students more fully and encourage critical thinking rather than rote applications of formulae. Incorporating history enables students, practitioners, and statisticians to treat the discipline as an ongoing endeavor, crafted by fallible humans, and provides a deeper understanding of the subject and its consequences for science and society.

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OBJECTIVES/SPECIFIC AIMS: Key factors causing irreproducibility of research include those related to inappropriate study design methodologies and statistical analysis. In modern statistical practice irreproducibility could arise due to statistical (false discoveries, p-hacking, overuse/misuse of p-values, low power, poor experimental design) and computational (data, code and software management) issues. These require understanding the processes and workflows practiced by an organization, and the development and use of metrics to quantify reproducibility. METHODS/STUDY POPULATION: Within the Foundation of Discovery – Population Health Research, Center for Clinical and Translational Science, University of Utah, we are undertaking a project to streamline the study design and statistical analysis workflows and processes. As a first step we met with key stakeholders to understand the current practices by eliciting example statistical projects, and then developed process information models for different types of statistical needs using Lucidchart. We then reviewed these with the Foundation’s leadership and the Standards Committee to come up with ideal workflows and model, and defined key measurement points (such as those around study design, analysis plan, final report, requirements for quality checks, and double coding) for assessing reproducibility. As next steps we are using our finding to embed analytical and infrastructural approaches within the statisticians’ workflows. This will include data and code dissemination platforms such as Box, Bitbucket, and GitHub, documentation platforms such as Confluence, and workflow tracking platforms such as Jira. These tools will simplify and automate the capture of communications as a statistician work through a project. Data-intensive process will use process-workflow management platforms such as Activiti, Pegasus, and Taverna. RESULTS/ANTICIPATED RESULTS: These strategies for sharing and publishing study protocols, data, code, and results across the spectrum, active collaboration with the research team, automation of key steps, along with decision support. DISCUSSION/SIGNIFICANCE OF IMPACT: This analysis of statistical methods and process and computational methods to automate them ensure quality of statistical methods and reproducibility of research.

Bioinformatic analysis of experimental and clinical proteomic data

SummaryProteomics, along with other omics, can be utilized as a tool of personalized medicine in order to understand the individual needs of patients better based on their expression levels of proteins. This type of personalized approaches are likely to be much more common in the future, since new diagnostic and therapeutic methods are constantly being developed and there is already currently a great need to select the most cost‐effective ones for each patient. For these reasons, a lot of effort is currently going into finding potential biomarkers through discovery studies. In addition to sample processing and advanced equipment, proteomic research also requires the work of statisticians and bioinformaticians as the research methods produce a growing amount of statistical data. Hence, methods of analyzing big data are also increasingly important and therefore researchers in bioinformatics field are both developing new methods and utilizing old ones in order to tackle the growing data. This course will focus on some of the most basic aspects of bioinformatics analysis of proteomic data and is aimed to provide clinicians and other researchers alike better understanding of the aspects important to the analysis.

A world without statistics?

A world without statistics?

Studying Africa's Large Numbers

Morten Jerven's work offers a historical perspective on the techniques used by national administrations and international organizations to quantify and analyze the growth of African economies. In his view, the work of statisticians and economists has largely failed to account for national economic and social realities since the beginning of the structural adjustment period. The informalization of economies, the weakness of statistical institutions, and the lack of methodological rigor among international experts have led to the production of statistical fictions. Jerven's analysis calls into question the usual narratives produced by quantitative economic history, such as that of an African economic failure since 1960. It also opens a dialogue with the sociology of quantification, highlighting cases where growth calculations appear arbitrary. However, his methodology suffers from a number of weaknesses. While his earliest works were based on detailed national case studies, Jerven's recent analyses have focused on the critique of continent-wide discourses, in particular international comparisons and econometric studies of growth. His work has thus moved away from a careful ethnography of numbers toward a focus on the denunciation of global practices. This shift prevents the author from making precise reflections on the various roles of numbers in African societies, the multiple positions and modes of action that quantification engages, or the specific historical trajectories which calculations of African growth are supposed to represent.

Bonesetting: the algebra of genocide

ABSTRACTGenocide rulings should not care about numbers. Legally, proving the intent to destroy a people in whole or in part is what counts. Yet numbers are vital actants in the often decades-long lead-up to trials. Aggregate numbers give weight to the specificity of individual testimony, statistical estimates can transform missing people into cold, hard facts, and algorithms can reveal ‘excess death’, even when forensic anthropologists cannot find all the bones. And because of this power, numbers are highly contested in both truth commission findings and trials like that of Generals Ríos Montt and Rodríguez Sánchez. In this article I analyse the disentangling work of statisticians and anthropologists in exhuming and counting bodies, and how particular numbers (200,000; 1,771; ninety-three per cent) are made, then re-entangled in efforts to count. The modern ideal of a universal subject of rationality and abstraction that positions women and natives as those who cannot count contributed to their historic exclusion and dehumanization. Counting, as in adding things up, is part of the historic achievement of the trial to make Maya-Ixil women and men count, in the sense of to matter.

Fuel for Growth and Development

Abstract World Statistics Day is the ideal time to showcase diverse applications of data, and how the work of statisticians is helping improve the lives of people around the world. The next 20 pages offer merely a glimpse of the full range of problems to which statistical analysis is applied, despite touching on a wide range of issues: from economic development to trade and transport, data sharing, human rights and hunger. We begin, though, with a special introduction from John Pullinger, the UK National Statistician and current chair of the UN Statistical Commission, on the importance of World Statistics Day

Comments on: Comparing and selecting spatial predictors using local criteria

We would like to congratulate the authors for producing this interesting and novel methodology for comparison of spatial fields. It is important that this problem be discussed and expanded, especially in the context of large data sets, which is undoubtedly one of the main challenges that any statistician working with environmental space– time data has to face in contemporary research.We have divided our comments in three sections that cover separate (albeit intertwined) topics. In Sect. 2, we link this work with previous literature on hypothesis testing with multiple predictors and discuss the consequences of not accounting for predictor uncertainty. In Sect. 3, we discuss the interpretability of Locally Selected Predictors (LSP) and Globally Selected Predictors (GSP) estimates and potential challenges around this issue, while in Sect. 4, we expand some points on oversmoothing and scalability for large data sets that have arisen in this work.

The comparability of quantitative surveys on sport participation in France (1967–2010)

Results from quantitative surveys enable historians, sociologists and demographers to describe and analyse the evolution of sport participation in France from 1967 to 2010. However, most of these social scientists use the results of these surveys to create very different methodologies without having studied the surveys’ empirical data or databases. In this article, we demonstrate how we have attempted to establish a basis for comparability of the surveys by analysing these databases. As a result of our work, certain affirmations on which the history of sport participation in France has long been based may be called into question or even changed. This comparison raises the question of the distinction between the work of statisticians on the one hand, and that of historians, sociologists and demographers on the other.

Making statistics understood . . . and getting it used

This month, the Journal of Physiology begins publishing a series of articles on good practice for presenting and analysing data from experimental studies. Several other journals will simultaneously publish the same articles. What better message could there be but the title of the first one: ‘Show the data, don't conceal them’? As a statistician working closely with clinical research colleagues, it frustrates me how often analyses are not clear in published articles, and how often the underlying data are not clear. This hampers both the convincingness of the paper's conclusions and – just as importantly – the value of the results found in helping to design further studies. So I urge all writers, for the benefit of your readers, please show us the data, don't conceal them. No-one says that statistics is easy. People used to say that; many used to dismiss it as a series of unhelpful and irrelevant mathematical operations that had little to do with interpreting data. They might then, typically, have proceeded to incorrectly interpret their data! Today, most sensible researchers see statistical methods as necessary, even if sometimes frustratingly opaque. If you fall into that category, you have my sympathy. It is a difficult subject often made more so by poor communication on the part of some of my statistician colleagues. Often I have been asked, ‘can't you write something simple on this subject?’ Well, it's not easy but that is what Gordon Drummond and Sarah Vowler have set out to do. A series of articles (one a month until around the middle of 2012) is planned, with a variety of authors contributing their skills and experience. Soon-to-appear topics include correlation and regression, analysing categorical data, sample size and power considerations, to list but a few. Similar types of article series have been published before. Examples include the series of Statistics Notes in the British Medical Journal (starting in April 1994 and currently at number 55); a series on Advanced Statistics articles in Academic Emergency Medicine (from 2002 to 2007); a series on Trials on Trial in the Medical Journal of Australia (2004–2005); and a series of Users' Guides to the Medical Literature in JAMA (1993–2010). A good starting point for these is to simply search for ‘statistics notes’ on http://www.bmj.com. There are other similar series too but clearly none has solved all of the problems for all of the authors (or readers). Continuously reinforcing the message will undoubtedly help. We encourage our authors to absorb the content of these new articles, thereby adding clarity to your writing. And we encourage readers to absorb the content too and help bring peer pressure to bear to improve the quality and usefulness of published research.

国際共同治験に関する統計的課題：製薬企業の統計家の立場から

The Japanese ‘drug lag,’ where drugs approved in US and EU are not approved in Japan, has been aggravated for many years. The bridging strategy has been accepted to utilize foreign clinical trial data in a new drug application since ICH E5 guideline was published in 1998, but the ‘drug lag’ was not improved. Instead of the bridging strategy, multinational clinical trials including Japan have been encouraged to promote efficient and rapid development of new drugs in Japan for recent several years. Although a global drug development strategy including Japan was changed, it is a fundamental issue that foreign clinical data have to be accepted as full or partial support for approval of a new drug application in Japan. For assuring that foreign clinical data can be extrapolated in other regions, it needs to consider what ethnic factors might affect on efficacy and safety of experimental drugs, how the influence from each ethnic factor should be evaluated, how many patients should be enrolled in each region participated in a global clinical trial, and so on. In this article, these issues are discussed from the point of view of a statistician working in a Japanese pharmaceutical company.