Cary Jim
Cary Jim holds a Ph.D. in Information Science with a concentration in Data Science. She brings a strong background in user research and analytics, applying a holistic approach to understanding user characteristics and behavior across diverse environments. Cary is passionate about leveraging data to drive meaningful insights and enjoys getting hands-on with the latest technology tools. Outside of work, she loves experimenting with new recipes in the kitchen and unwinding with British detective shows.
議程
Stratified sampling helps ensure representative data subsets, especially when working with imbalanced groups. In this talk, we’ll explore its use in survey analysis, demonstrate Python-based implementation, and share best practices for improving data reliability and reducing bias. Attendees will gain a clear understanding of when and how to use stratified sampling effectively in real-world scenarios.