Multiple Hypothesis Testing and Its Applications
STA4515 (Graduate Only)
Fall 2018
README FIRST
- This is one of the "4500 level courses that are 0.25FCEs and last 6 weeks" offered in
the Department of Statistical Sciences.
- Objective: provide an in-depth understanding of (single and multiple) hypothesis
testing in the context of big data and data science.
- Audience: graduate students with solid training in statistics or biostatistics.
Although application examples involve statistical genetics and genomics, knowledge in
statistical genetics is not required. Examples will be presented in a self-sufficient way.
GENERAL INFORMATION
- Time: Thursdays 10-1pm (The six lectures will be held on Oct 25, Nov 1, 8, 15, 22 and
29).
- Location: UC-D301.
- Instructor: Lei Sun (sun@utstat.toronto.edu)
- Office hour: half hour before and after each session.
- Format of instruction: Lectures.
- Evaluation: in-class presentation and take-home (research-focused) project. Details to be announced during the first lecture.
COURSE SYLLABUS AND LECTURE NOTES
- The old-fashioned blackboard and chalk sticks will be used during the lectures combined
with notes in .pdf format and handouts.
A central issue in many current large-scale scientific studies is how to assess
statistical significance while taking into account the inherent multiple hypothesis testing
issue. This graduate course will provide an in-depth understanding of the topic in the
context of data science with a focus on statistical `omics' studies. We start with an insightful
revisit of single hypothesis testing, the building block of multiple hypothesis testing. We
then study the fundamental elements of multiple hypothesis testing, including the control of
family-wise error rate and false discovery rate. We will also touch upon various more
advanced topics such as data integration, selective inference and fallacy of p-values. The
course will provide both analytical arguments and empirical evidence. Students are evaluated
based on class participation and one final research report on a suggested or self-selected
project related to multiple hypothesis testing.