DAY 1 | Tuesday, May 24
1-4 p.m. CDT | WORKSHOP – Statistical Language Modelling with R
Dr. Dave Campbell, Carleton University & Bank of Canada
ATTEND IN PERSON or ONLINE
Senate Chamber, E3-262 EITC, Fort Garry Campus, University of Manitoba OR via Zoom (link distributed after registration)
Analysis of numeric and categorical data has unlocked incredible insights over the past century. However, tools for these data types are not amenable to the contents of legal documents, news briefings, emails, product descriptions, or social media posts. Text data requires a different set of tools to extract descriptive insights and test hypotheses. This workshop will use R and Tidyverse tools to showcase statistical language modelling tools through hands-on tutorials outlining common use cases. Extensions and more complex modelling approaches will be outlined along with their costs, risks, and potentially more meaningful insights. The first half of the workshop will focus on sentiment analysis; producing descriptive statistics and performing hypothesis tests. The second half will focus on clustering documents. Bring a computer with RStudio (version >2021.09.0) and R (version >4.1) installed and be prepared to run the analysis live during the workshop. Code and datasets will be provided for the hands-on workshop.
Prerequisite: Familiarity with Base R and/or Tidyverse
About Dr. Dave Campbell
Dr. Dave Campbell is computational statistics methodologist with a penchant for collaboration and a strong interest in ensuring student employability. He is a full Professor in the School of Mathematics and Statistics and the School of Computer Science at Carleton University and also the Assistant Director of Data Science Applications at the Bank of Canada.
Before moving to Ottawa in 2019, Dave was an Associate Professor at Simon Fraser University in the Department of Statistics and Actuarial Science, where he led the creation of their BSc in Data Science. He was the inaugural President of the Data Science and Analytics Section of the Statistical Society of Canada and a co-organizer of the Vancouver Learn Data Science Meetup (>5000 members).
Dr. Campbell researches inferential algorithms at the intersections of statistics with machine learning, computing, and applied mathematics to solve problems in forensic science, environmental toxicology, paleo-climatology, psychology, economics, and more. He has co-authored discussion papers in Bayesian Analysis and the Journal of the Royal Statistical Society (series B) and been awarded over $3.5 million in research grants. His recent projects include identifying orcas from underwater acoustic hydrophones and predicting when they will cross into shipping lanes (funded by the Department of Fisheries and Oceans), improving uncertainty quantification methods for nuclear magnetic resonance (funded by the National Research Council of Canada), and developing inferential statistical language processing tools for quantifying covariate effects in language. At Carleton he supervises a team of grad students and post-doctoral fellows. At the Bank of Canada he is often hiring new recruits with strong computing and statistics skills. Find him on LinkedIn.
4-5 p.m. CDT | VIRTUAL STUDENT POSTER SESSION – Research innovations in Statistics and Data Science
Registration Deadline May 13, 2022
As part of the CANSSI Prairies Summit on May 24–25, the CANSSI Prairies Regional Centre is holding a Student Poster Competition. The competition is open to undergraduate and graduate students at all universities in Manitoba and Saskatchewan. We invite submissions about methodological and applied research in statistical and data sciences from all disciplines. Cash prizes will be awarded for top posters.
You have a choice of participating in either a virtual or an in-person poster session. Note that the in-person poster session will be on Day 2 (May 25, 2022)
Download a copy of the competition instructions/guidelines here: http://www.canssi.ca/wp-content/uploads/2022/05/Poster-Competition-Instructions.png
REGISTER FOR THE POSTER COMPETITION HERE: Register Here