Protected learning content
Understanding Outliers in Data Files
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- Capability outcome
- Critical principle: a potential outlier is a question
- What competence looks like
- Before you begin
- Module 1 - Define the decision before the method
- Practical Lab 1 - File intake and analysis charter
- Module 2 - Profile the file before detecting outliers
- Module 3 - Visual exploration and distribution shape
- Practical Lab 2 - Produce a visual profile
- Module 4 - Univariate detection methods
- Module 5 - Contextual, multivariate and time-based anomalies
- Practical Lab 3 - Compare two methods responsibly
- Module 6 - Investigation, root cause and disposition
- Module 7 - Privacy, bias and safe communication
- Practical Lab 4 - Investigate and present five findings
- Module 8 - Reproducibility, review and operationalisation
- Practical Lab 5 - Reproducible analysis package
- Capstone - Defensible outlier investigation from a data file
- Official reference set