[ugrads] [grads] Applied Mathematics Research Showcase: Statistics

Kan Zhang kzhang23 at hawk.iit.edu
Wed Mar 7 17:19:50 CST 2018


 Hello All,

Please join us *Thur**sday, March 08*, for *free lunch* and a chance to see
what's new in the Applied Mathematics department!

This is part of a series of special seminars that IIT's SIAM student
chapter and Applied Mathematics department host jointly. Each seminar
features faculty members briefly discussing their recent and ongoing
research over lunch. If you are a new graduate student or an advanced
undergraduate looking for research topics or advisors, or if you just want
to know what your colleagues are working on, then this event is for you.

This seminar will feature research in *Statistics*, with a talk by Dr. Lulu
Kang.The talk will take place on *Thursday, March 08, 12:45-1:45* in room *RE
106*. Lunch will be provided. It is open to all, but Applied Mathematics
students are strongly encouraged to attend. We hope to see you there!

Title: Discrepancy-Based Design for A/B Testing Experiments



Abstract:

The aim of this talk is to introduce a new design of experiment method for
A/B tests. A/B tests (or "A/B/n tests'') refer to the experiments conducted
to estimate the treatment effect(s) of a two-level or multi-level
controllable experimental factor. To conclude whether the treatment effect
is significant, the common practice is to use a completely randomized
design and perform the hypothesis test on the sample difference-in-mean
estimate.  However, such estimator is not always accurate when the
covariates of the test units affect the responses, especially for the small
to medium-sized experiments. To overcome this issue, we propose the
discrepancy-based design which significantly improves the accuracy of the
estimates of the treatment effects, as shown both theoretically and through
simulations.  More importantly, the design approach is model-free, and thus
it makes the estimation robust to the model assumption.  Also, it can be
applied to both continuous and discrete/categorical types of responses. We
develop two optimization procedures to minimize the discrepancy criterion
for both offline and online experiments.



Sincerely,
Kan Zhang
IIT SIAM Student Chapter Secretary
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