Rich data sets

What does research suggest about teaching statistics using rich data sets?

Rich data sets – which may be messy, have many variables (multivariate), a complex structure, and a mixture of both qualitative and quantitative data – may support student engagement and create opportunities for cross-curricular work
Approaches such as exploratory data analysis, informal inference, and data modelling are complementary to working with rich data sets
Using rich data shifts the focus of statistics lessons away from procedural fluency towards interpretation and discussion and so may require different approaches to assessment
When using multivariate data, it is important to use contexts with which students are familiar, access to carefully designed software tools, and well-structured activities
When engaging with rich data a problem-solving cycle approach is recommended
Rich, multivariate data sets should contain a range of different data types to allow the posing of interesting and engaging questions and problems

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