Sampling

This course is designed to introduce the essentials of sampling, probability and survey methodology. This includes simple probability samples, stratified sampling, cluster sampling, dealing with non-response, estimating and survey quality. You will consider the theoretical foundations of different sampling approaches, as well as practical applications of this knowledge in contexts such as market research, political polling and the Canadian census. Analysis using the R programming language will also be highlighted, drawing on skills developed in Introduction to R.

Requirements

This course is designed for those who have a degree in something other than Computer Science/Statistics and are looking to enhance their data science skills for their career.

This course draws on the skills you developed in Introduction to R.

Learning Outcomes

The ability to implement simple probability samples
The ability to understand more complicated sampling procedures and the tradeoffs involved
The ability to identify and understand sources of error or inaccuracies in data as a result of sampling strategies
The development of intuition around survey quality

Delivery Format and Schedule

TBC