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"An original account of willful ignorance and how this principle relates to modern probability and statistical methods Through a series of colorful stories about great thinkers and the problems they chose to solve, the author traces the historical evolution of probability and explains how statistical methods have helped to propel scientific research. However, the past success of statistics has depended on vast, deliberate simplifications amounting to willful ignorance, and this very success now threatens future advances in medicine, the social sciences, and other fields. Limitations of existing methods result in frequent reversals of scientific findings and recommendations, to the consternation of both scientists and the lay public.Willful Ignorance: The Mismeasure of Uncertainty exposes the fallacy of regarding probability as the full measure of our uncertainty. The book explains how statistical methodology, though enormously productive and influential over the past century, is approaching a crisis. The deep and troubling divide between qualitative and quantitative modes of research, and between research and practice, are reflections of this underlying problem. The author outlines a path toward the re-engineering of data analysis to help close these gaps and accelerate scientific discovery. Willful Ignorance: The Mismeasure of Uncertainty presents essential information and novel ideas that should be of interest to anyone concerned about the future of scientific research. The book is especially pertinent for professionals in statistics and related fields, including practicing and research clinicians, biomedical and social science researchers, business leaders, and policy-makers"--

A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects. Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation pre

In 1939, George Gallup's American Institute of Public Opinion published a pamphlet optimistically titled The New Science of Public Opinion Measurement. At the time, though, survey research was in its infancy, and only now, six decades later, can public opinion measurement be appropriately called a science, based in part on the development of the total survey error approach. Herbert F. Weisberg's handbook presents a unified method for conducting good survey research centered on the various types of errors that can occur in surveys-from measurement and nonresponse error to co

If at one time we thought that the movement to science would yield unification of the discipline, it is now apparent that there are many roads to science. Still it is important for us to consider yet again what the appropriate goals are for our scientific enterprise. What works in theory building; induction and deduction; prediction and control; the search for useful principles to guide us - examining these questions, we can build a better science. Political science has come so far as a discipline that different schools and scholars have different interpretations of science in the study of pol

ABSTRACTThe publication ofThe American Voterin 1960 revolutionized the study of American voting behavior. Its University of Michigan authors, Angus Campbell, Philip E. Converse, Warren E. Miller, and Donald E. Stokes, were to share thousands of citations, but they were four different people, with different backgrounds, different personalities, and different career trajectories afterwards. This paper presents a chronological biography ofThe American Voter, from assembling the research team, through writing the book, to its aftermath, and ending with brief perspectives on each author.