Quantitative Analysis of Social Problems (Behavioral Science)

WHY THIS IS IMPORTANT: Tufte shows how to examine data for quality and "truthiness". Tufte also shows how to "design" information to turn meaningless data into meaningful, usable information--which could improve your career, or help the war on "Fake News". Due to the cost-cutting elimination of many fact-checkers and overseers of information quality & ethics in newsagencies, corporations, and schools, many people are losing important tools for critical thinking ie. being able to tell or comprehend "real truths" versus "fake" information. This affects everybody's freedom by manipulating the public, voting, and whether they can protect themselves from fraudsters. ABSTRACT: Solving Social Problems using data analysis; Intro to How to use Data Analysis, Predictions and projections: some issues of research design... "PREFACE If you want to understand and solve social problems, a good first step toward these goals is to master the quantitative ideas in this collection Of papers. The readings show What quantitative analysis is good for and how it can be Criticized and improved. Included, then, are a number of well-executed studies of important social, economic, and political problems: equality of educational opportunity, voting behavior, poverty, automobile accidents, smoking and health, and so forth. Other papers center on data analysis, research design, and statistical criticism. Many Of the papers either are published here for the first time or have been relatively inaccessible. Thus the collection should prove enlightening to those who want access to the more quantitative studies Of social problems as well as to those studying statistics and data analysis in the social sciences. The collection is divided into five parts: *Statistical Evidence and Statistical Criticism. *Experimental and Quasi-Experimental Studies. *Economic and Aggregate Analysis. *Survey Data. *Data Analysis and Research Design. The first three readings are careful and judicious assessments of quantitative work. They discuss controversial and sometimes difficult studies: Sexual Be- havior in the Human Male by Kinsey, Pomeroy, and Martin; a political tract called "Catholic Voters and the Democratic National Ticket"; and studies of the relationship between smoking and lung cancer. The fourth paper in this section, growing out of some of the criticisms of the research on smoking and health, suggests a number of ground rules for statistical criticism. All these readings are valuable, it seems to me, because, by their example, they help us to arrive at sensible evaluations of quantitative studies. The discussion by Cochran, Mosteller, and Tukey Of "Sexual Behavior in The Human Male" reaches a balanced conclusion about a flawed but highly significant study. The paper by Cornfield, Haenszel, Hammond, Lilienfeld, Shimkin, and Wynder pulls together many different types of evidence about the consequences of smoking. Their work is especially valuable because of its stress on the logic of inference and the logic of counterexplanation. ………. " ------------------ Edward Rolf Tufte (born 1942 in Kansas City, Missouri to Virginia and Edward E. Tufte), a professor emeritus of statistics, graphic design, and political economy at Yale University has been described by The New York Times as "the Leonardo da Vinci of Data". He is an expert in the presentation of informational graphics such as charts and diagrams, and is a fellow of the American Statistical Association. Tufte has held fellowships from the Guggenheim Foundation and the Center for Advanced Studies in Behavioral Sciences. Tufte currently resides in Cheshire, Connecticut. He periodically travels around the United States to offer one-day workshops on data presentation and information graphics. http://www.edwardtufte.com

Beyond its central premise, the book can be read through the connected lenses of Nonfiction. Those themes offer useful points of attention as the characters, ideas, or world develop, especially where the book complicates the expectations of its primary category.