Date of Award
2018
Publisher
North Dakota State University
Document Type
Thesis
Degree Awarded
Master of Science (MS)
Program
Statistics
Department
Statistics
College
Science and Mathematics
Faculty Advisor
Magel, Rhonda
Description
This research examines the power of the Kolmogorov-Smirnov two-sample test. The motivation for this research is a large data set containing soil salinity values. One problem encountered was that the power of the Kolmogorov-Smirnov two-sample test became extremely high due to the large sample size. This extreme power resulted in statistically significant differences between two distributions when no practically significant difference was present. This research used resampling procedures to create simulated null distributions for the test statistic. These null distributions were used to obtain power approximations for the Kolmogorov-Smirnov tests under differing effect sizes. The research shows that the power of the Kolmogorov-Smirnov test can become very large in cases of large sample sizes.
Recommended Citation
Larson, Lincoln Gary, "Investigating Statistical vs. Practical Significance of the Kolmogorov-Smirnov Two-Sample Test Using Power Simulations and Resampling Procedures" (2018). Statistics. 30.
https://digitalcommons.ndsu.edu/stats/30
Rights
NDSU Policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Author ORCID Identifier
0000-0003-3855-4431
Handle Identifier
https://hdl.handle.net/10365/28770