Modern Techniques for Survey Sampling and Complex Data

Why Study Survey Sampling?

Canada’s population is widely diverse, and survey data needs to be representative of our population. If industry, government and academia use biased data to make data-driven decisions, it can negatively impact Canadians in critical and sometimes unforeseen ways.

Modern survey sampling reduces selection biases, better representing the target population of interest. It prevents researchers from using convenient, uncontrolled big data sources. 

Areas of Exploration

Selection Bias

Includes examining the implications of selection bias in survey sampling.

Classical Sampling Techniques

Includes reviewing classical survey sampling techniques and identifying potential entry points for selection biases. 

Modern Survey Sampling

Includes bridging the gap between classical methods and modern statistical tools to better control big data. 

Solving Global Challenges

Research Team’s Goal

To improve modern survey sampling and reduce selection biases in large data sources.