Multiclass Prediction and Inference: A Practical Approach

Approaches To Teaching The Analysis Of Large-Scale And Complex Data

2024 SSC Annual Meeting in St. John’s

Sponsor: Statistical Education Section

Date: Wednesday, June 5, 2024.

Speaker: G. Alexi Rodríguez-Arelis, PhD

alexrod@stat.ubc.ca

Affiliation: Assistant Professor of Teaching, UBC

Regression modelling is a vast statistical field comprising various approaches that might suit different inferential and predictive practical cases. In this context, when teaching data analysis in an accelerated data science graduate program, it is crucial to establish an efficient and homogeneous workflow that can cater to a wide range of regression approaches using data science-based reproducible tools (such as Jupyter notebooks) along with engaging datasets. This talk will explain this analysis workflow while providing crucial insights on its application in a regression graduate course beyond ordinary least squares. Finally, under an inferential and predictive scenario, this teaching approach will be exemplified via a specific model targeted to multiclass nominal responses: multinomial regression.

This website contains a Quarto presentation.