
MathEd Forum 

October 26, 2016  
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10:00 a.m.  10:10 a.m. Reports: OAME, OMCA, OCMA, CMS, and other. 10:10 a.m.  11:10 a.m. SHORT DESCRIPTION: In the ancient world chance was often contrasted
with the absence of cause (Polybius) or Fate's unalterable necessity
(Tacitus). Despite the widespread use then of randomization (and
somewhat surprisingly for a civilization capable of producing Ptolemy's
Almagest), there was no calculus of chances. After the 1654 FermatPascal
correspondence, mathematical probability finally emerged, but at
first only in the restrictive setting of equally likely cases. SHORT BIO: Sandy Zabell is a Professor of Mathematics and Statistics
at Northwestern University. His book "Symmetry and Discontents"
(Cambridge University Press, 2005) is a collection of a number of
his papers on the history and philosophical foundations of probability
and statistics. His applied interests include the DNA identification,
forensic science, and the legal applications of statistics. 11:10 a.m.  11:40 a.m. SHORT DESCRIPTION: Surely that day has come! But what statistical thoughts are needed
for efficient citizenship? One could argue that uncertainty about
causality is at the root of most current social, political and scientific
controversies. Does human activity cause climate change? How will
changes in fiscal policy affect economic recovery? Does using cell
phones increase the risk of cancer? In almost every case, controversy
subsists because causal information is needed from data that are
largely observational as opposed to experimental. Students of statistics
learn the dictum "correlation is not causation," a truism
that doesn't help them develop the finer judgment necessary to evaluate
imperfect evidence from observational data that is often all that
is available to inform crucial and urgent issues. SHORT BIO: Georges Monette is an Associate Professor in the Department
of Mathematics and Statistics at York University. He obtained his
Ph.D. at the University of Toronto in statistical inference. He
has had a long association with York's Statistical Consulting Service
and has worked on applications of statistics in a wide range of
disciplines. Consulting is a form of teaching in which complex concepts
need to be conveyed to collaborators and clients who often have
little statistical and mathematical background. In addition to teaching
academic courses, he teaches workshops on statistical visualization
and longitudinal data analysis. 11:40 a.m.  12:10 p.m. SHORT DESCRIPTION: Continuing with the theme of the importance of statistical thinking for efficient citizenship, we appeal for increased emphasis in our mathematics curricula on randomness, risk, and reasoning rationally in the presence of uncertainty. In particular, we will consider ideas for expanding the study of statistics in schools beyond graphical and numerical summaries of data and we will show some important recent work about how we can support sophisticated inferential reasoning in very young students. SHORT BIO: Alison Gibbs is a teachingstream faculty member in
the Department of Statistics at the University of Toronto. Before
beginning her graduate work, she taught secondary school mathematics
in Ontario. After completing her Ph.D., she held postdoctoral and
Assistant Professor positions at York University. In her current
position she has taught a variety of probability and statistics
courses, ranging from a firstyear seminar in statistical literacy
to a graduate course in statistical consulting. Her responsibilities
also include overseeing and advising the department's Statistical
Consulting Service. Her research interests are in applications of
statistics, particularly in nutrition studies, and in the development
of the full range of skills required of professional statisticians.
She is currently the chair of the Statistical Education Committee
of the Statistical Society of Canada. The panellists will describe their experiences from different levels of schooling in Pakistan, Sri Lanka and Czech Republic. 12:10 p.m. 1:00 p.m. LUNCH BREAK 1:00 p.m. 2:00 p.m.

