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
| LEC 1 | TR 17:00 - 19:45
| TI STUDIODE
| Wenjun Jiang | | |
| Notes: Please refer to your Student Centre for fees associated with this class. This information will be available before the first day of classes. |
This course will be offered next in
Winter 2024.