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Welcome to the Department of Statistics and Actuarial Science

The Department of Statistics and Actuarial Science is a top tier academic unit among statistical and actuarial science globally. Our students and faculty explore topics such as Actuarial Science, Biostatistics, Data Science, Quantitative Finance, Statistics, & Statistics-Computing. Our department is home to:

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full-time faculty researching diverse and exciting areas

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undergraduate students from around the world

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 graduate students in Master, Doctoral, and professional programs

Interested in graduate studies with Statistics and Actuarial Science? Meet Mingyu (Bruce) Feng, a PhD student in actuarial science. Bruce is a pioneer researcher in the field of sustainable investment and the impact of climate change. Learn more about furthering your education on the Future Graduate page on the Math site.

  1. June 4, 2020Dylan Spicker, winner at the SSC 2020 Case Studies in Data Analysis Competition
    Winner Dylan Spicker and teammate Melissa Van Bussel

    Congratulations to Dylan Spicker (University of Waterloo) and team member Melissa Van Bussel (Carleton University) in their first place finish for their work on Case Study #2: Predicting podcast popularity in iTunes at the Statistical Society of Canada (SSC) 2020 Case Studies in Data Analysis Competition. Dylan is currently a SAS PhD student studying in the field of Statistics.  

    To learn more about this competition, please visit the SSC competition website.

  2. May 20, 2020Shixiao Zhang winner of the SSC 2020 Pierre Robillard Award
    Shixiao Zhang

    Shixiao Zhang is this year’s winner of the Pierre Robillard Award of the Statistical Society of Canada (SSC) which recognizes the best PhD thesis in probability or statistics defended at a Canadian university in a given year. His thesis, entitled “Multiply Robust Empirical Likelihood Inference for Missing Data and Causal Inference Problems," was written while Shixiao was a doctoral student in the Department of Statistics and Actuarial Science at University of Waterloo under the supervision of Dr. Peisong Han and Dr. Changbao Wu.

  3. May 19, 2020New Springer Book by Changbao Wu and Mary Thompson
    Thompson & Wu

    Professors Changbao Wu and Mary Thompson, Department of Statistics and Actuarial Science at the University of Waterloo, have a new book entitled “Sampling Theory and Practice” published by Springer.

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  1. June 25, 2020Department seminar by Guillaume Saint-Jacques, Linkedin

    Fairness through Experimentation: Inequality in A/B testing as an approach to responsible design

    As technology continues to advance, there is increasing concern about individuals being left behind. Many businesses are striving to adopt responsible design practices and avoid any unintended consequences of their products and services, ranging from privacy vulnerabilities to algorithmic bias. We propose a novel approach to fairness and inclusiveness based on experimentation. We use experimentation because we want to assess not only the intrinsic properties of products and algorithms but also their impact on people. We do this by introducing an inequality approach to A/B testing, leveraging the Atkinson index from the economics literature. We show how to perform causal inference over this inequality measure. We also introduce the concept of site-wide inequality impact, which captures the inclusiveness impact of targeting specific subpopulations for experiments, and show how to conduct statistical inference on this impact. We provide real examples from LinkedIn, as well as an open-source, highly scalable implementation of the computation of the Atkinson index and its variance in Spark/Scala. We also provide over a year's worth of learnings -- gathered by deploying our method at scale and analyzing thousands of experiments -- on which areas and which kinds of product innovations seem to inherently foster fairness through inclusiveness.

    The details to connect to this seminar will be available in the near future. 

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Meet our people

Ruodu Wang

Ruodu Wang

Associate Professor; University Research Chair

Contact Information:
Office: M3 3122
Phone: 519-888-4567, ext. 31569

Ruodu Wang's personal website