Contributed Paper C100
Enabling Students to Transitioning Beyond the Basics to Understanding and Assimilation
PresenterTimothy E. O'Brien (US)
Students and practitioners with a basic/introductory background in applied statistics often find it challenging to transition into courses such as regression analysis, experimental design, modelling, and categorical and survival data analysis. Through a series of carefully chosen illustrations based on distributions, hypothesis testing, interval estimation, statistical modelling, and likelihood, this paper exhibits how students and applied researchers can best bridge this gap. Since these methods also serve to unify disparate-seeming statistical methods, this sequence of demonstrations also helps individuals to make important over-arching connections, and appreciate juxtapositions and contrasts, while maintaining the big picture. Key illustrations are discussed in addition to our experiences using these in the classroom. Computational methods as well as SAS and R software are highlighted and illustrated.