NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ892389
Record Type: Journal
Publication Date: 2010
Pages: 19
Abstractor: As Provided
Reference Count: 21
ISSN: ISSN-1069-1898
Teaching Rank-Based Tests by Emphasizing Structural Similarities to Corresponding Parametric Tests
Derryberry, DeWayne R.; Schou, Sue B.; Conover, W. J.
Journal of Statistics Education, v18 n1 2010
Students learn to examine the distributional assumptions implicit in the usual t-tests and associated confidence intervals, but are rarely shown what to do when those assumptions are grossly violated. Three data sets are presented. Each data set involves a different distributional anomaly and each illustrates the use of a different nonparametric test. The problems illustrated are well-known, but the formulations of the nonparametric tests given here are different from the large sample formulas usually presented. We restructure the common rank-based tests to emphasize structural similarities between large sample rank-based tests and their parametric analogs. By presenting large sample nonparametric tests as slight extensions of their parametric counterparts, it is hoped that nonparametric methods receive a wider audience. (Contains 2 figures and 7 tables.)
American Statistical Association. 732 North Washington Street, Alexandria, VA 22314. Tel: 703-684-1221; Tel: 888-231-3473; Fax: 703-684-2037; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education
Audience: Teachers
Language: English
Sponsor: N/A
Authoring Institution: N/A