Compiling Toward an Understanding of Sampling Distributions

This paper presents a novel independent learning experience and details evidence of its effectiveness. The learning experience presented here empowers students to better understand the sampling distribution identity and the Central Limit Theorem. This improved understanding is thought to be derived from the active role that students play in assembling sampling distributions. The valuable hands-on experience requires negligible effort on the part of the instructor. The assignment is ready to use and also completely customizable. Additionally, the student output generates a convenient plagiarism check resulting from time seeded random sampling. The assignment was designed for use within a business curriculum. Access to Excel and a basic understanding of Excel operations are sufficient for student success. Results suggest that this experience improved student understanding of the sampling distribution identity.