The Role of Synthetic Data in Teaching and Learning Statistics

The use of synthetic data is increasingly of interest to teachers and learners of statistics. Real world data has obvious advantages but limitations that may be less obvious. Though we live in a world of “big data,” sourcing real world datasets that satisfy the needs of teachers may not be easy. In many situations, synthetic data can offer a viable alternative to real world data for teaching and learning statistics. Our basic premise is that datasets—real world and synthetic—should be relevant to learning objectives, offer students a degree of realism, and be sufficiently rich to encourage learning beyond the immediate context. We offer guidelines for generating synthetic datasets to ensure all three dimensions are satisfied: relevance, realism, and richness.