top banner top banner
index
RegularArticles
ReplicationStudies
SpecialIssues
Vignettes
EditorialBoard
Instructions4Authors
JournalGuidelines
Messages
Submission

Search publications

Using Dynamic Graphics to Teach the Sampling Distribution with Active Learning

Full text PDF
Bibliographic information: BibTEX format RIS format XML format APA style
Cited references information: BibTEX format APA style
Doi: 10.20982/tqmp.17.2.v001

Hoisington-Shaw, Kathryn J. , Pek, Jolynn
v1-v9
Keywords: dynamic graphics , sampling distribution , active learning , web application , Central Limit Theorem
(no sample data)   (no appendix)

The sampling distribution and the Central Limit Theorem (CLT) are the basis for many statistical procedures and inferences. Despite their ubiquitous nature in statistics, these concepts are some of the most abstract and difficult for students to understand. To foster a deeper understanding of these concepts, a web-based application was created that uses dynamic graphics to illustrate the concepts and engage students with active learning. We provide an outline of three in-class activities using the web application to promote the learning of population distributions, simple random sampling, sampling variability, the idea of a statistic, the sampling distribution, the Law of Large Numbers, and the CLT. These in-class activities tie the concepts together and place emphasis on their role as building blocks of statistical inference. By linking abstract theoretical concepts together before introducing statistical inference, the web application facilitates statistical thinking that students can utilize both inside and outside the classroom.


Pages © TQMP;
Website last modified: 2021-06-22.
Template last modified: 2019-03-03>.
Page consulted on .
Be informed of the upcoming issues with RSS feed: RSS icon RSS