Design of surveys and data collection, bias and efficiency of surveys. Sampling weights and variance estimation. Multi-way contingency tables and introduction to generalized linear models with emphasis on applications.
This course may not be repeated for credit.
Prerequisite(s)
- Data Science 601, 602, 603, 604 and admission to the Graduate Diploma in Data Science and Analytics, or the Master of Data Science and Analytics.
Sections
This course will be offered next in
Spring 2024.