Spring 2025
Details/registration for Spring 2025 QMWS courses will be available in
Introduction to Structural Equation Modeling
Instructor: Cathy Zhang, PhD (xijuan@yorku.ca)
Structural equation modelling (SEM) is an advanced statistical technique that allows exploration of complex relationships among variables by combining elements of confirmatory factor analysis (CFA) and multiple regression. SEM is commonly used in social and behavioural sciences. In this four-day workshop, I will explain the methodology underlying CFA and SEM and demonstrate how to perform these analyses using R software. This workshop is ideal for students, researchers, and practitioners familiar with basic regression and R coding who wish to learn more advanced statistical modelling techniques.
Dates/Times: June 3-6 (4 days), 2:30 pm - 4:00 pm
Format: Online (Zoom)
Cost: $30
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Introduction to R
Instructor: Hannah Tran, MA (tranhan@yorku.ca)
This workshop is designed to introduce R and RStudio to those with a basic understanding of statistics. Students will first gain familiarity with the RStudio layout and environment, including learning basic commands, the utility of R packages, and how to import/export datasets. We will then learn how to use RStudio to explore, manipulate, and clean data. Students will also learn how to run basic descriptive statistics and basic inferential statistical analyses, as well as understand how to interpret this output. Finally, students will learn how to create visualizations and utilize R Markdown to communicate their statistical findings.
Dates/Times: May 26-28 (3 days), 11:30 am - 2:30 pm
Format: Online (Zoom)
Cost: $45
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Introduction to Simple and Multiple Linear Regression in R
Instructor: Veerpal Bambrah, MA (bambrahv@yorku.ca)
This 3-week workshop will focus on conducting simple linear regressions and multiple linear regressions, including moderation analyses, in R, with an additional focus on how to write up these results in a research paper. In this workshop, participants will learn when and how to conduct, interpret, visualize, and write up the results of: a) A simple linear regression and multiple linear regression, including performing regression diagnostics, and b) Moderation analyses, specifically 2-way interactions. This course is intended for participants who possess little-to-no experience with conducting statistical analyses and presenting statistical results, or who possess an elementary understanding of linear regression but would like to build on this understanding by conducting and interpreting moderation analyses. This course will be taught in R, so participants should have introductory experience with this software. Note: The use of your own laptop or computer will be necessary for this course. It is also necessary to have R and RStudio installed on your laptop or computer. These softwares are free and can be found at the following links: R for macOS: https://cran.r-project.org/bin/macosx/; R for Windows: https://cran.r-project.org/bin/windows/base/; RStudio: https://posit.co/download/rstudio-desktop/. Please see the following video for help downloading and installing RStudio: https://www.youtube.com/watch?v=YrEe2TLr3MI
Dates/Times: June 12, 19, and 26, 2:00 pm to 5:00 pm
Format: Online (Zoom)
Cost: $45
Eligible for a Digital Credential: No
Registration: Click Here to Register
Introduction to Equivalence Testing (Negligible Effect Testing)
Instructor: Victoria Celio (MA Psychology)
Teaching Assistant: Tatijanna Martel (BA Psychology)
There are many instances where researchers are interested in testing hypotheses concerning negligible effects. For example, a researcher may be interested in investigating whether male and female students are equivalent on test anxiety, or whether test anxiety is negligibly correlated with test performance. Unfortunately, traditional null hypothesis significance testing (NHST) is not valid for testing hypotheses concerning negligible effects. One method for testing hypotheses concerning negligible effects is through the Equivalence Testing (ET) framework (also known as Negligible Effect Significance Testing, NEST). This workshop provides an introduction to ET/NEST, including how to apply and interpret using the negligible package from R.
Dates & Times: June 18 and 25 (11:30 am - 1:30 pm)
Format: Online (Zoom)
Cost: $20
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Some courses offered through the QMWS permit students to receive a Digital Credential/Badge for completing the course. There is no cost to you in order to receive the Digital Credential/Badge. For more details please see Digital Credentials.
To see a list of past QMWS workshops, visit our Archives Page
