Nathan Taback
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Nathan Taback

Assistant Professor, Teaching Stream


I am an Assistant Professor, Teaching Stream in Statistical Sciences at the University of Toronto and the Director of Data Science Programs.

I received my Ph.D. in statistics from the University of Toronto. I work on: innovations in statistics education that involve student motivation and engagement with an emphasis on experiential learning; and projects that involve statistical design, data analysis, and communication. These projects have been in a number of areas including medicine, law, journalism, and ecommerce.


Current Teaching

Winter 2018: STA130 - An Introduction to Statistical Reasoning and Data Science. The course website is available here here.

Fall 2017: STA220 - Course coordinator. Fall 2017 information about different sections of STA220 is available here.

Fall 2017: STA4002HF - Data Science, Collaboration, and Communication (grad). The course website is available here here.

Past Teaching

Introduction to Machine Learning in the Digital Humanities

Digital Humanities Summer Institute 2017, University of Victoria (with Paul Barrett)

This course takes an introductory approach to machine learning in digital humanities topics. Participants will learn essential concepts in machine learning and use machine learning tools to collect and analyze literary, historical, and social media data sets using a number of machine learning approaches. The course will include an optional introduction to the R programming language; knowledge of this language will provide students with an opportunity to develop their own machine learning algorithms. In addition to the technical dimension of machine learning, we will also discuss the hermeneutic challenges posed by machine learning to the digital humanities, particularly as technical decisions enable specific ways of engaging in humanities scholarship: In what ways do DH scholars need to be cautious about the 'results' offered by machine learning algorithms, and what is the relationship between those results and humanities forms of knowledge?

Class notes and code in R Notebooks are available here.

Some members of the 2017 DHSI ML Class

Introduction to the Practice of Statistics - STA220

Design of Scientific Studies - STA305H1/STA1004

Class notes can be found here.

Check out a draft of my book on the Design of Experiments and Observational Studies here.

Statistical Consulting - STA2453

Class website can be found here.

Statistical Consultation, Communication, and Collaboration - STA490

Introduction to Statistical Theory - STA255


A/B Testing. Dec. 6, 2017. Amazon Science Cafe. Toronto


Coming soon


Coming soon



account_balance Department of Statistical Sciences
Sidney Smith Hall
100 St.George Street
Toronto, Ontario, Canada
M5S 3G3

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