What Do Students Need to Know to Understand Sampling Distributions, and How Well Do They Know It?

• Activity Number: 550
• Type: Topic Contributed
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Consulting
• Author(s): Tisha Hooks*+ and Michael Posner and Michelle Sisto and Dale Berger
• Companies: Winona State University and Villanova University and International University of Monaco and Claremont Graduate College

Abstract

Statistical inference is typically the primary learning objective in an introductory course in statistics. Sampling distributions play a vital role in understanding how inferences are made, yet students often fail to achieve understanding and demonstrate proficiency of this important topic. Moreover, as recognized by Chance, delMas and Garfield (2004), students also sometimes fail to comprehend some important prerequisite concepts, which may hinder their ability to understand sampling distributions. Based on the work of Chance et al. (2004) this work examines three categories of prerequisite knowledge for sampling distributions: the ideas of sampling, variability, and distributional thinking. The authors have worked toward the development of an assessment tool that can be used to provide instructors with quick feedback on the understanding and misconceptions of sampling distributions and prerequisite concepts. In this session, we will present the results from a study investigating students' understanding of both sampling distributions and the prerequisite knowledge components.