Preface

Abstract

Since 1979, Teaching Statistics has aimed to emphasize good practice in teaching statistical thinking in any context, whether in statistics or in other disciplines such as economics and business, biology and health sciences, engineering and information technology, psychology, mathematics, and any area which uses statistics. Teaching Statistics seeks to inform, enlighten, stimulate, guide, correct, inspire, entertain, and encourage. The Teaching Statistics Trust was established to publish it, and it arose from the International Statistical Education newsletter for International Statistical Institute (ISI) members. Other initiatives from the ISI's Education Committee, established in 1948, led, at the same time, to the first International Conference on Teaching Statistics (ICOTS) in 1982, and the committee itself became the International Association for Statistical Education in 1992. Statistics emerged in the 1700s as a discipline focused on collecting data to describe the demographic and economic situation of the state, as the basis for political action. In the mid-1800s and early 1900s, there was a coming together of people from very varied backgrounds, intent on solving practical problems (eg, associated with economics, health, weather, and the human condition), the emergence of statistical societies, and a creative blossoming of mathematical models (often associated with inference). However, too many curricula have set these early models in aspic and simply demand technical mastery from students, with no concern for working with authentic data or modeling per se. The core ideas of multidisciplinarity, addressing important problems, inventing models, and proposing actions, have been displaced by the pursuit of decontextualized mathematical skills. Data science is a wake-up call to retrieve the heritage of statistics. As long advocated by professional statisticians and leading statistical educators, good practice in teaching statistics should reflect the practice of statistics in the fullest sense of “greater statistics” as described by Chambers in 1993 [1] and data analysis as described by Tukey in 1962 [4], integrating principles of data investigations with statistical literacy for all, as described by many including Rumsey in 2002 [3]: