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Looks at the connections between census‐taking, border‐making, and identity‐formation in the Soviet Union. It focuses on the All‐Union Census of 1926, which was the first census to categorize the entire population of the USSR according to ‘nationality.’ It analyses the process through which ethnographers and statisticians used their expertise to formulate a census question about nationality and to create an official definitional grid. Also focuses on the activation of official nationality categories on the ground in Central Asia. In particular, it looks at how self‐identified Tajik and Uzbek leaders used the occasion of the census to mobilize their populations and vie for contested territories.

This chapter provides the answers to the issue of how to use a statistician. As such, the aim of this chapter is to show researchers how statisticians may be able to help with the research, how researchers can provide help that statisticians need, and how the researchers can benefit from their contact with a statistician.

This chapter unearths a series of heretofore largely forgotten exchanges between Chinese and Indian statisticians. It is based on study of key figures, such as the deputy director of China's State Statistics Bureau, Wang Sihua, and the Indian statistician P. C. Mahalanobis. Focusing on Chinese interest in the emerging technology of large-scale random sampling, in which Mahalanobis and the Indian Statistical Institute were global innovators, the exchanges point to alternative frameworks for Cold War scientific exchanges while also placing in stark relief the extent to which Chinese statisticians and leaders clearly understood both the strengths and shortcomings of their own statistical system. The chapter traces these exchanges, explaining their timing and the motivation behind them. Each set of actors in these exchanges had its own agenda. The chapter shows that the Indians were particularly keen on learning more about China's planning methods.

Essentially presents what the title indicates. Also included are a variety of jokes about statistics and statisticians as well as a bit of statistical history describing the important contributions of Francis Galton (1903).

It never was the case that only statisticians work with statistics, but the occupational landscape is becoming more and more diverse. This chapter looks at the work of statisticians and data scientists, but also at how journalists, campaigners, and academics such as economists and psychologists work with statistics, and how the resulting variety of approaches and orientations shapes the discipline of statistics and how it is seen. I consider the following questions. First, who analyses what data? In particular, how do two relatively new occupations, data scientist and data journalist, fit in? Second, who presents the results to which audiences, and in particular, how are statistical findings communicated to the general public? Third, who defines what statistical analyses are appropriate, and to what extent is the ‘replication crisis’ really a crisis for statistics? Fourth, who trains whom in working with data, and how might that depend on the influence of data science? None of these questions have straightforward answers. There have been and continue to be changes in all of them. They all involve people who would not be described, by themselves or others, as ‘statisticians’.

This chapter deals with a specific dimension of the boundaries of finance: the mediation of value judgments by securities analysts. It traces the emergence of chartists as a specific group in relation to the new kind of price data generated by the stock ticker. Occasional and unsystematic evaluation of securities had always taken place, and financial information had always been collected, more or less systematically. The new price data, however, boosted efforts to predict future prices movements and, with them, the value of securities. Some brokers left financial transactions and moved into price interpretation. They diligently began selling their intellectual product around, and so technical analysis was thus born. The chapter examines, how using memoirs, letters, journal articles, and manuals, a group of former brokers and statisticians successfully marketed price charts and technical analyses to investors and stock brokers alike. Contrary to the assumption that the growing complexity and mass of financial information required this sort of cognitive intermediation, it shows here how intermediaries created a demand for this sort of product.

This introductory chapter introduces a “crisis of counting” during the early years of the People's Republic of China (PRC). In its simplest form, the crisis in the PRC was understood as a problem of building a centralized statistical system. At the heart of the varied solutions attempted by Chinese statisticians was a contentious debate about the very nature of social reality and the place and efficacy of mathematical statistics—in particular, probability theory—in ascertaining that reality. This debate played out against a backdrop populated by three divergent methodological approaches to statistics and statistical work. After all, abstract ideas about the nature of the world, whether defined by chance or certainty, have real world consequences. Chinese deliberations over such questions and their engagement with the Ethnographic, Exhaustive, and Stochastic approaches during the 1950s exemplify some of those consequences. The chapter unpacks these choices and traces how statistics in its various forms—as a (social) science, as a profession, and as an activity—came to be formulated and practiced, shedding light on fundamental questions germane to the histories of the People's Republic, statistics and data, and mid-century science.

This chapter examines the ‘legitimating’ process: that is to say the selective use of social science in justifying policy and practice. It focuses on the policies of evidence. It examines the political factors in the construction, publication and use of evidence generated by applied social science. It shows how political factors always enter into these processes and reviews the implications of this for applied social research in general. It notes that many, but not all, academics have ‘willingly’ entered into this process, sometimes in terms of ideological assertion (this is particularly true of economists), sometimes in relation to funding opportunities. It also notes that some civil servants, and in particular statisticians, have an honourable record in resisting the pressure for ‘good news and only good news’ and discusses how the examples of statistics commissions provide a basis for ‘honest’ applied social research.

This chapter discusses the statisticians at the NIH and their role in the establishment of the different components of the Cancer Chemotherapy National Service Center (CCNSC). It also discusses the French statistical approach to clinical trials at the National Hygiene Institute and the Gustave-Roussy Institute. The development of the sequential analysis and the phase system is also examined.

This chapter examines data centers, statisticians, data managers, and collaborators within cooperative oncology groups who took over the management of clinical trials and their results. It also discusses the applications of statistics in clinical cancer trials, the design of multicenter trials, the stratification of treatment randomization by institutions, the advent of computerized techniques, and the introduction of organizational innovations by statisticians.

This chapter examines the statistical representation in Alfred Kinsey’s Sexual Behavior in the Human Male (SBHM), presents a history of statistics in the United States that ends with postwar sampling theory, and analyzes Kinsey’s interaction with the statisticians. It suggests that while Kinsey’s study prompted the imagination of new normative ideals for a national survey of sex, he also articulated resistance to the statisticians’ ideas concerning the use of a sample of the national population.

The quality of statistical data and availability on people with citizenship status problems are assessed in this chapter, which also examines state signatories data relevant to the United Nations human rights conventions. Statisticians’ involvement in developing guidelines for reports on international human rights instruments is discussed, as is the availability of the national statistical sources for people with citizenship status concerns. The use of administrative sources and population statistics for assessing the needs, characteristics, and number of people with citizenship concerns is also explored. The chapter concludes that the protection regime for people with citizenship concerns can be strengthened if statisticians cooperate with the human rights community.

This chapter presents a luncheon address at the conference by Jack E. Triplett. Triplett reviews the measurement problems on which Griliches worked; those on which he did not work directly but on which he had a significant influence; and those that will likely continue to be important in the future. He also discusses in greater detail Griliches's interactions with government economists and statisticians in the various statistical agencies. Triplett emphasizes that Griliches's impact on measurement and his leadership in the measurement community as a whole extended far beyond his immediate research, influencing his many students and colleagues (and their students and colleagues).

This chapter examines the emergence of the Data Science function and the considerations in developing such a function in a firm. Also presented are insights on how firms can best recruit and retain data scientists in an organization. The chapter examines the advantages and drawbacks of keeping the Data Science function embedded in a business functional area versus its own centralized function. The role and significance of the Chief Data Scientist and the Chief Analytical Officer are described and best practices for establishing a Chief Data Science office examined. Sample job descriptions for a Data Scientist and a Chief Data Scientist are provided. Best practices for maximizing the impact of Data Science in the enterprise are presented.

This chapter considers developments leading up to the census of 1850, heralded as the “first scientific census” of the United States. It made a clean break with its predecessors and solidified the influence of the reformer statisticians who found in it a way to make up for the catastrophic census of 1840. The most important change was the shift from the familial level for collection of information to individual data: a whole line of the principal schedule was devoted to each member of a family. The other great innovation was the division of the census into six separate schedules: free inhabitants; slaves; mortality (information on persons who had died during the past year); agriculture; manufactures; and social statistics (taxes; numbers of schools, of newspapers, of churches; criminality; and libraries within the district). Enumerating slaves led to intense political debates in Congress in the context of the sectional crisis.

This chapter focuses on the relationship between the Census Bureau and African Americans. In the first half of the twentieth century, the history of the agency’s relations with the black population was one of an incomplete transformation. For the census, blacks were the most objectified inhabitants, to the point that slaves were deprived of names to become numbers in the population statistics, and the ones least likely to be viewed as subjects. At the same time, blacks as a category were always the object of particular attention in census reports. The chapter also describes the growing involvement of black authors and statisticians in publications for the black population; the career of Charles E. Hall with respect to the census, who became the first African American to be given supervisory responsibilities over black employees; and the Census Bureau’s relations with the African American business community.