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An essential work on the origins of statistics The Rise of Statistical Thinking, 1820–1900 explores the history of statistics from the field's origins in the nineteenth century through to the factors that produced the burst of modern statistical innovation in the early twentieth century. Theodore Porter shows that statistics was not developed by mathematicians and then applied to the sciences and social sciences. Rather, the field came into being through the efforts of social scientists, who saw a need for statistical tools in their examination of society. Pioneering statistical physicists and biologists James Clerk Maxwell, Ludwig Boltzmann, and Francis Galton introduced statistical models to the sciences by pointing to analogies between their disciplines and the social sciences. A new preface by the author looks at how the book has remained relevant since its initial publication, and considers the current place of statistics in scientific research.
Emphasizing the debt of science to nonspecialist intellectuals, Theodore Porter describes in detail the nineteenth-century background that produced the burst of modern statistical innovation of the early 1900s. Statistics arose as a study of society--the science of the statist--and the pioneering statistical physicists and biologists, Maxwell, Boltzmann, and Galton, each introduced statistical models by pointing to analogies between his discipline and social science.
An essential work on the origins of statistics The Rise of Statistical Thinking, 1820–1900 explores the history of statistics from the field's origins in the nineteenth century through to the factors that produced the burst of modern statistical innovation in the early twentieth century. Theodore Porter shows that statistics was not developed by mathematicians and then applied to the sciences and social sciences. Rather, the field came into being through the efforts of social scientists, who saw a need for statistical tools in their examination of society. Pioneering statistical physicists and biologists James Clerk Maxwell, Ludwig Boltzmann, and Francis Galton introduced statistical models to the sciences by pointing to analogies between their disciplines and the social sciences. A new preface by the author looks at how the book has remained relevant since its initial publication, and considers the current place of statistics in scientific research.
A foundational work on historical and social studies of quantification What accounts for the prestige of quantitative methods? The usual answer is that quantification is desirable in social investigation as a result of its successes in science. Trust in Numbers questions whether such success in the study of stars, molecules, or cells should be an attractive model for research on human societies, and examines why the natural sciences are highly quantitative in the first place. Theodore Porter argues that a better understanding of the attractions of quantification in business, government, and social research brings a fresh perspective to its role in psychology, physics, and medicine. Quantitative rigor is not inherent in science but arises from political and social pressures, and objectivity derives its impetus from cultural contexts. In a new preface, the author sheds light on the current infatuation with quantitative methods, particularly at the intersection of science and bureaucracy.
Karl Pearson, founder of modern statistics, came to this field by way of passionate early studies of philosophy and cultural history as well as ether physics and graphical geometry. His faith in science grew out of a deeply moral quest, reflected also in his socialism and his efforts to find a new basis for relations between men and women. This biography recounts Pearson's extraordinary intellectual adventure and sheds new light on the inner life of science. Theodore Porter's intensely personal portrait of Pearson extends from religious crisis and sexual tensions to metaphysical and even mathematical anxieties. Pearson sought to reconcile reason with enthusiasm and to achieve the impersonal perspective of science without sacrificing complex individuality. Even as he longed to experience nature directly and intimately, he identified science with renunciation and positivistic detachment. Porter finds a turning point in Pearson's career, where his humanistic interests gave way to statistical ones, in his Grammar of Science (1892), in which he attempted to establish scientific method as the moral educational basis for a refashioned culture. In this original and engaging book, a leading historian of modern science investigates the interior experience of one man's scientific life while placing it in a rich tapestry of social, political, and intellectual movements.
"This book presents a comprehensive, insightful survey of the history of probability, both in terms of its scientific and its social uses. . . . It represents a substantial contribution not only to the history of probability but also to our understanding of the Enlightenment in general".--Joseph W. Dauben, "American Scientist".
This magnificent book is the first comprehensive history of statistics from its beginnings around 1700 to its emergence as a distinct and mature discipline around 1900. Stephen M. Stigler shows how statistics arose from the interplay of mathematical concepts and the needs of several applied sciences including astronomy, geodesy, experimental psychology, genetics, and sociology. He addresses many intriguing questions: How did scientists learn to combine measurements made under different conditions? And how were they led to use probability theory to measure the accuracy of the result? Why were statistical methods used successfully in astronomy long before they began to play a significant role in the social sciences? How could the introduction of least squares predate the discovery of regression by more than eighty years? On what grounds can the major works of men such as Bernoulli, De Moivre, Bayes, Quetelet, and Lexis be considered partial failures, while those of Laplace, Galton, Edgeworth, Pearson, and Yule are counted as successes? How did Galton’s probability machine (the quincunx) provide him with the key to the major advance of the last half of the nineteenth century? Stigler’s emphasis is upon how, when, and where the methods of probability theory were developed for measuring uncertainty in experimental and observational science, for reducing uncertainty, and as a conceptual framework for quantitative studies in the social sciences. He describes with care the scientific context in which the different methods evolved and identifies the problems (conceptual or mathematical) that retarded the growth of mathematical statistics and the conceptual developments that permitted major breakthroughs. Statisticians, historians of science, and social and behavioral scientists will gain from this book a deeper understanding of the use of statistical methods and a better grasp of the promise and limitations of such techniques. The product of ten years of research, The History of Statistics will appeal to all who are interested in the humanistic study of science.
Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
"In the early 1800s, a century before there was any concept of the gene, physicians in insane asylums began to record causes of madness in their admission books. Almost from the beginning, they pointed to heredity as the most important of these causes. As doctors and state officials steadily lost faith in the capacity of asylum care to stem the terrible increase of insanity, they began emphasizing the need to curb the reproduction of the insane. They became obsessed with identifying weak or tainted families and anticipating the outcomes of their marriages. Genetics in the Madhouse is the untold story of how the collection and sorting of hereditary data in mental hospitals, schools for 'feebleminded' children, and prisons gave rise to a new science of human heredity. In this compelling book, Theodore Porter draws on untapped archival evidence from across Europe and North America to bring to light the hidden history behind modern genetics. He looks at the institutional use of pedigree charts, censuses of mental illness, medical-social surveys, and other data techniques--innovative quantitative practices that were worked out in the madhouse long before the manipulation of DNA became possible in the lab. Porter argues that asylum doctors developed many of the ideologies and methods of what would come to be known as eugenics, and deepens our appreciation of the moral issues at stake in data work conducted on the border of subjectivity and science. A bold rethinking of asylum work, Genetics in the Madhouse shows how heredity was a human science as well as a medical and biological one"--Jacket.
This book goes beyond the methods usually covered in introductory textbooks on quantitative methods in tourism. It considers key issues in data selection, approaches to factor and cluster analysis and regression before covering advanced topics including structural equation modelling, maximum likelihood estimation, simulation and agent-based modelling. The result is a guide to quantitative methods in tourism that de-mystifies both simple and apparently complex techniques and makes them more accessible to tourism researchers.