Fall 2025
Full details/registration for Fall 2025 QMWS courses will be available soon!
Introduction to Bayesian Analysis in JASP
Instructor: Katherine Newman, PhD candidate (kmnewman@yorku.ca)
Description: Master the free, point-and-click statistical software that has become a standard in psychological research. This workshop provides a practical introduction to JASP, an intuitive platform designed to run advanced analyses without programming. We will use JASP to demystify and apply Bayesian statistics, a powerful framework that moves beyond simple p-values to quantify evidence for your hypotheses directly. Through hands-on exercises with a provided dataset, you will become proficient using JASP’s environment while learning to execute its Bayesian modules for correlations, t-tests, and ANOVA. The session will focus on interpreting JASP’s unique outputs (e.g., Bayes Factor and robustness plots) and understanding how they better inform your findings by quantifying evidence, rather than relying on significance thresholds. To illustrate the real-world impact of this framework, the workshop will conclude with a research spotlight on a cutting-edge application: how Bayesian modeling is used in neuroscience to create personalized maps of brain function. This approach, which would not be possible with traditional statistics, is a critical step towards the future of personalized medicine, where interventions can be tailored to a person’s unique neurological function. This workshop is essential for students at all levels who seek to strengthen their analytical skill set, enhance their research for theses and dissertations, and align with contemporary methodological standards. Leave with the practical skills to implement these sophisticated analyses in JASP right away. After this workshop, you will be able to: 1) Confidently navigate and use JASP for statistical analysis; 2) Perform and interpret Bayesian correlations, t-tests, and ANOVA in JASP; 3) Understand and report Bayes Factors for your hypotheses; 4) Compare Bayesian and frequentist results side-by-side within a single software platform; 5) Articulate the value of Bayesian methods for complex, hierarchical problems in research. Familiarity with basic statistical procedures (e.g., t-tests, p-values) is required. No coding or prior Bayesian experience is needed. Please install the free JASP software (jasp-stats.org) for your operating system before attending.
Dates/Times: November 20 (12:00-1:30 PM)
Format: Online (Zoom)
Cost: $7.50 + tx
Eligible for a Digital Credential: No
Registration: Click Here to Register
Introduction to R
Instructor: Hannah Tran (tranhan@yorku.ca)
Description: This workshop is designed to introduce R and RStudio to new users 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 then 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: October 23, October 30, and November 6 (11:30-2:30 PM)
Format: Online (Zoom)
Cost: $45 + tx
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Introduction to jamovi
Instructor: Maria Orlando, MA (morlando@yorku.ca)
Description: This workshop is an introduction to jamovi (https://www.jamovi.org/), a free and open-sourced software for statistical analysis. jamovi is user-friendly and features a point-and-click interface, making it ideal for those who are new to statistical software. In this two-session workshop, you will learn how to use jamovi to describe, analyze, and interpret data. Session 1 will cover using jamovi for descriptive statistics to summarize data. Session 2 will explore using jamovi for inferential statistics to interpret data. Each session includes hands-on activities using real datasets, giving you the opportunity to practice your skills and apply them to your own data beyond the workshop. The focus of this workshop is using jamovi, so a general understanding of statistical concepts is recommended but not required.
Dates/Times: November 5 and 12, 11:30 - 2:30 PM
Format: Online (Zoom)
Cost: $30 + tx
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Intermediate R
Instructor: Gabriel Crone, MA (gc2001@my.yorku.ca)
Description: Many introductory R courses focus on the fundamentals and often overlook important concepts that help R users become better coders. This workshop empowers participants to expand their R programming skills and develop stronger coding workflows. Over three days, participants will build fluency in core R skills and data manipulation using the Tidyverse (Day 1); learn to write functions, apply iteration techniques, and explore R package development (Day 2); and master reproducible workflows with RProjects, RMarkdown, and GitHub (Day 3). This workshop is designed for intermediate R users—those with roughly six months to two years of experience or who have completed an introductory R course. Advanced users with extensive programming or package development experience may find the content more of a refresher. By the end, participants will be equipped with a suite of tools to become more versatile, knowledgeable, and confident R coders.
Dates/Times: November 13, 20, & 27, 11:30 - 2:30 PM
Format: Online (Zoom)
Cost: $45 + tx
Eligible for a Digital Credential: Yes
Registration: Click Here to Register
Leveraging Large Language Models (LLMs) and Prompt Engineering for Research
Instructor: Cathy Zhang, PhD (xijuan@yorku.ca)
Description: If you are curious how Large Language Models (LLMs) and prompt engineering can make your research more efficient, then this workshop is for you. This workshop introduces you to LLMs and the basics of prompt engineering. You will learn how to use ChatGPT to support key research tasks, including literature reviews, data cleaning, coding, and academic writing.
Dates/Times: Friday, Dec 12, 4:00 pm - 6:30 pm.
Format: Online (Zoom)
Cost: $12 + tx
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
