Speaker: Prof. Eric Kolaczyk (Boston University)

Hosted by the University of Calgary Biostatistics Centre (UCBC) via Zoom (Free)

Sponsored by Canadian Statistical Science Institute (CANSSI); O’Brien Institute for Public Health, University of Calgary; Statistical Society of Canada

Date and time
Tuesday February 22, 2022, 9:00 a.m.–12 p.m. (MST), and
Wednesday February 23, 2022, 1:00–4:00 p.m. (MST)

Registration link:

https://ucalgary.zoom.us/meeting/register/tJYvc-2qqD8oGNeFza2ObMKgXwWQQEVOIl6d

Speaker introduction: Dr. Eric Kolaczyk is a professor in the Department of Mathematics and Statistics at Boston University, and currently serves as director of the university's Hariri Institute for Computing. He is a founding member of Boston University's new Faculty for Computing and Data Science, and holds affiliated appointments with the Division of Systems Engineering, the Bioinformatics Program, and the Program in Computational Neuroscience.

Abstract
This series of lectures will serve as an introduction to statistical analysis of network data and consist of five parts:
(i) an introduction to background and terminology;
(ii) basic elements of network visualization and characterization;
(iii) a hands-on session in R covering visualization, characterization, and an introduction to community detection;
(iv) regression and prediction on networks; and
(v) uncertainty quantification of characteristics from noisy network data.

Examples will be drawn broadly from various domain areas, with particular emphasis on networks in bioinformatics, computational neuroscience, and social network analysis. Material for the first four parts will be presented at the level of Kolaczyk and Csardi (2020)*. The last will be drawn largely from recent research.

*Reference:  Kolaczyk, E.D., & Csardi, G. (2020). Statistical analysis of network data in R, 2nd ed. Springer, New York.

Prerequisite
No background in networks is necessary, although a reasonable level of knowledge in statistics will be assumed.