← This weekAnalysisData engineering & the warehouse/lakehouseSASThe article discusses evaluating the multivariate t cumulative distribution function (CDF) in SAS, highlighting the classical multivariate normal (MVN) distribution as a standard model for correlated data. It notes the simplicity and intuitive parameters of the MVN model, while acknowledging that the assumption of normality is not always applicable.
MyDataWork POV — SAS's approach to evaluating the multivariate t CDF is a boon for data professionals dealing with correlated data. The MVN model's simplicity is its strength, making it accessible for analysts who need to quickly fit data without getting bogged down in complexity. While normality assumptions can be restrictive, SAS offers a pragmatic path forward, allowing for nuanced analysis in real-world scenarios. This is a reminder that effective data work hinges on assembling the right tools for the task, rather than relying on a monolithic solution.
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