Introduction to synthetic data for the social sciences

Description: This module provides a foundational-level conceptual understanding of synthetic data. It explains key concepts and terminology, introduces common approaches to generating synthetic data, and explores the opportunities and limitations of synthetic data in research contexts. It does not cover technical implementation. 

Level: Foundational

Learning objectives:

By the end of the module, you will be able to:

•      Define synthetic data and explain key concepts and terminology.

•         Explain the concept of fidelity and its importance in synthetic data.

•         Identify potential uses of synthetic data in social science research.

•         Describe common methods for generating synthetic data.

•         Recognise the importance of documentation and metadata for interpreting and using synthetic data.

·       Intended Audience: This module is designed for social science researchers and data service professionals who are new to synthetic data.

Pre-requisites: No prior understanding of synthetic data is required. A basic understanding of statistical concepts will be helpful.

⏲ Approx. 60 minutes