Plenaries

Plenary 1: On the relationships between statistics and other subjects in the K-12 curriculum

Zalman Usiskin

Sixty years ago, statistics barely touched the school experience of a typical student. In the study of social science, students might encounter data. In a science laboratory experience, students might collect data. In a mathematics classroom, students would be expected to know how to calculate the mean of a data set. In contrast, today it is becoming prevalent to expect increasing numbers of students to learn several measures of central tendency and spread, to encounter theoretical and actual distributions, and to discuss topics such as randomness, statistical tests, and statistical significance that in the past were introduced at the college level. As one of the mathematical sciences, the more intensive study of statistics in grades K-12 naturally has been considered as a part of the school mathematics curriculum. This has great advantages, as mathematics is the second most important academic school subject, behind reading and language arts. But as statistics has become more important, its connections with everyday literacy, science, and the social sciences suggest consideration of statistics across the curriculum in addition to a reconsideration of its relationships with classical mathematical areas of arithmetic, algebra, geometry, and analysis.

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Plenary 2: What can we learn from real-world communication of risk and uncertainty?

David Spiegelhalter

Risk-communication is a hot topic, whether it concerns the benefits and harms of screening or the chance of a catastrophic earthquake. It is challenging to explain both unpredictability and uncertain knowledge to the public, and yet these are also essential elements in education in probability and statistics. I shall argue that current approaches in communicating risk and uncertainty can contribute substantially to educational practice.

In particular, Gigerenzer’s recommendation for ‘natural frequencies’ – whole-number outcomes starting from a defined population of cases - can be adapted to teaching probability based on a natural sequence of stages: empirical multiple narratives from experimentation represented as 2-way tables and frequency trees, to expected outcomes in multiple future experiments, and finally to probability trees. Issues of relative and absolute risk continually arise in topical stories, and representations that make these transparent are as relevant in the classroom as in the news.

Any predictions of expected outcomes will depend on assumptions, and in practice P-values are used (and often misused) to inform the public about evidence against hypotheses, say regarding the Higgs Boson or Paul the Psychic Octopus. This Fisherian idea neatly starts to integrate probability and observation, with likelihood ratios arising as the natural measure for deciding between competing hypotheses.

Examples of public communication, and classroom materials, will be used to illustrate these ideas.

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Plenary 3: Teaching statistics to Real People: adventures in social stochastics

Rachel Fewster

Students arrive in our first undergraduate course in statistical theory with many different backgrounds and motivations: from mathematically able students in their first year at university, to math-phobes who have put off the dreaded theory course to the last possible moment in their degree programme. One thing unites all these students: they are real people, immersed in their own worlds and biologically programmed to be social learners. Over the last few years I have tried to put Homo socialis to pedagogical advantage by experimenting with team-based activities in class tutorials. I will outline some of the successes and failures, from illustrating p-values through animated cartoons to a never-to-be-repeated investigation into the carpet-buttering tendencies of dropped toast. Importantly, I will discuss the ramifications of social learning for developing capacity for solo thinking and study. While there are obvious advantages of teamwork for fostering versatile thinkers who can alternate between language, diagrams, and mathematical notation, I will suggest that there are also more subtle effects at play. An abstract problem that has been discussed in a group automatically becomes a real-world experience. I will show how a classroom game to “catch the spies” translated on a final exam to a mature understanding of maximum likelihood estimators, suggesting that the classroom activity provided the tools for students to reach a deep understanding once they were “home alone” in private study.

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Plenary 4: Statistics in 2014: Reflections on the occasion of the 175th anniversary of the American Statistical Association

Ronald Wasserstein

The ASA is celebrating its 175th anniversary during 2014, with a big celebration planned at the Joint Statistical Meetings in Boston just a couple of weeks after ICOTS. Indeed, there is much to celebrate about our profession, and about the successes of the second oldest professional society in the United States. It is a great time to be a statistician! But there are challenges ahead, too. We’ll talk about the state of the statistical profession, and possible impacts on the teaching of statistics.

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Plenary 5: Sustainable education for professional Statisticians

Pedro Luis do Nascimento Silva

Statistics as a profession is facing increasing challenges from reality:

• Big data and the associated revolution in data availability, accessibility, speed of production and pressure to “do something” with the available data;
• Artificial intelligence, machine learning, data mining and many other trends where the “art and science” of data analysis, modeling and inference are being taken up by software which is evolving at a very fast pace, and which aims to depend less and less on the competence and skills of the users;
• Increasing costs of traditional education via in-person courses;
• Fast evolution of methodology and technology, demanding increasing investment of time and effort to keep up with the developments;
• Ever wider areas of application of Statistics with their own dialects, and their promotion of “do-it-yourself” by practitioners who do not possess broad statistical education, but who master very complex and specialized statistical tools (models, methods and software) relevant to their fields.

Given such challenges, how can statistics education deliver Statisticians who can thrive in these challenging times and help keep them “fit” throughout their careers? In this talk we consider some ideas to meet this challenge.

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