Workshop

Linear regression models, also known as linear models, are essential tools in various fields due to their simplicity and ease of interpretation. This workshop offers a comprehensive introduction to both simple and multiple linear regression.

What You'll Learn:

• Fundamentals of regression models and their assumptions
• How to interpret coefficients and conduct significance testing
• Exploring interactions between variables and using dummy variables
• Model-checking techniques, including residual plots and collinearity diagnostics
• Methods for model selection

Are you ready to transform messy datasets into clean, structured insights? This workshop introduces you to dplyr -- a powerful R package for data manipulation.

Through practical examples, you’ll discover how to:

• Combine multiple operations seamlessly with pipes

• Select and arrange columns and rows for clarity

• Filter and group data to uncover patterns
• Summarize and transform datasets for analysis

Whether you’re a beginner or looking to sharpen your skills, you’ll have the confidence to manage data like a pro and streamline your analysis by the end of the workshop. 

Learn how to use Qualtrics to create and launch a survey. The goal of this workshop is to provide an overview of the whole process along with some hands-on exercises. The workshop will start with instructions on how to build a survey, then will cover getting it ready for the field, and finish with showing users how to distribute, monitor, and extract their data.

Registration is free to all students, faculty and staff at the University of Waterloo.

In this workshop, we aim to provide a practical introduction to statistical methods used for comparing group means, including various types of t-tests, analysis of variance (ANOVA), and post-hoc analysis techniques. Participants will learn when and how to apply independent and paired t-tests, interpret ANOVA results, and choose appropriate post-hoc tests to explore significant findings. Through examples and hands-on exercises, attendees will gain confidence in selecting and executing the suitable statistical tests for their data.

This workshop provides a comprehensive review of fundamental statistical concepts using the R software. Participants will revisit key topics such as descriptive statistics, probability distributions, hypothesis testing, and basic inferential statistics. The session includes practical exercises in R to reinforce understanding and application of these concepts.

Join us for an introductory workshop to R, where you’ll learn the fundamentals of this powerful open-source language.

Registration is free and open to all University of Waterloo faculty, staff, and students (both graduate and undergraduate). No prior programming experience is required.

Count data, which consists of non-negative integers, is commonly collected and analyzed in fields like epidemiology, genomics, and clinical research. This workshop will introduce you to Poisson regression, a powerful tool for modelling count data over time.

Linear regression models, also known as linear models, are essential tools in various fields due to their simplicity and ease of interpretation. This workshop offers a comprehensive introduction to both simple and multiple linear regression.

Data often comes in the form of tables or databases, making it challenging to understand beyond their sizes and variable types. This workshop will introduce you to graphical and numerical techniques to uncover the structure of your data.

A binary variable is one that has only two possible outcomes, such as yes/no, success/failure, or 0/1. In this workshop, participants will learn how to estimate and make inferences about binary response probabilities using logistic regression, a powerful tool widely used in various fields such as healthcare, marketing, and social sciences. Registration is free and open to all University of Waterloo faculty, staff, and graduate students.