This lecture covers various model selection methods in biostatistics, including sequential testing, backward elimination, forward selection, stepwise selection, and the use of AIC and adjusted R2. The instructor explains how to choose the best model among multiple candidates and the importance of starting with a sensible model guided by biological knowledge.