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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.

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.