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Though the workshop will not go into mathematical details and proofs, it will provide some reasoning and intuition behind the key formulas used in survey sampling. It will also look at various examples using the statistical software SAS (free to students, faculty and staff at the University of À¶Ý®ÊÓƵ). In addition to illustrating basic data analysis techniques, those examples aim to provide guidance on some of the pitfalls of analyzing survey data. Part 3 is a practical hands-on opportunity for participants to conduct basic data analysis using SAS on their own laptop.

This two-day workshop will be held in DC 1568. Registration is free for all members of the university.

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 À¶Ý®ÊÓƵ faculty, staff, and graduate students.

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.

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.

In this one-day workshop and drawing on Dr. Sarah Wilkins-Laflamme’s 10+ years of experience running national and international surveys, we will review the key steps in developing high-quality survey questions and questionnaires along with tips for achieving precise, relevant and accessible measures when collecting survey data via smartphone, tablet, computer, in-person interview, telephone interview and mail. There will be a number of hands-on activities throughout this workshop for constructing new survey measures as well as for improving examples of existing survey measures brought by the workshop participants themselves and drawn from the International Social Survey Programme’s 2024 module on digital societies.

The workshop will be held in DC 1568. Registration is free for all students, faculty and staff at the University of À¶Ý®ÊÓƵ.

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.

Join a panel of experts for a thought-provoking conversation on the impact of bots and fraudulent data in survey research. We’ll explore best practices for detecting and preventing bot participation, identifying and cleaning fraudulent data, and addressing the challenges posed by imposter respondents.