[Join us for Part 2 of our Survey Data Essentials series with Joy Liu: Sampling Design — Reaching the Right People.
Explore practical sampling approaches and learn how representativeness and bias can shape the reliability of your results.
Collecting a large amount of data does not necessarily mean collecting good data. This introductory session explores how to define a target population, select an appropriate sample, and understand how sampling choices affect the quality and representativeness of the resulting data. Participants will be introduced to common sampling approaches, sources of bias, and practical considerations for data collection.
Series Takeaways
- Learn how to design surveys and questions that produce clear, reliable, and useful data;
- Learn how to select an appropriate sample and recognize factors that can affect the representativeness and quality of your data; and
- Learn how to turn survey responses into meaningful insights through data preparation, visualization, and basic statistical analysis.
PART 3 | Register Here
Meet Your Presenter - Joy Liu, Dalhousie University
Joy is a data-driven researcher with expertise in transforming complex datasets into clear, actionable insights using R, SQL, and advanced analytical tools.
Her work focuses on statistical modelling, data quality, and translating technical findings into accessible information that supports informed decision-making. With strengths in research, technical communication, and emerging AI-supported approaches, Joy brings a thoughtful and analytical perspective to helping organizations better understand their data and apply it effectively.