Investigating Statistical vs. Practical Significance of the Kolmogorov-Smirnov Two-Sample Test Using Power Simulations and Resampling Procedures
| dc.contributor.author | Larson, Lincoln Gary | |
| dc.description.abstract | 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. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Investigating Statistical vs. Practical Significance of the Kolmogorov-Smirnov Two-Sample Test Using Power Simulations and Resampling Procedures | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2018-08-03T14:18:51Z | |
| dc.date.available | 2018-08-03T14:18:51Z | |
| dc.date.issued | 2018 | en_US |
| dc.identifier.uri | https://hdl.handle.net/10365/28770 | |
| dc.identifier.orcid | 0000-0003-3855-4431 | |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Science and Mathematics | en_US |
| ndsu.department | Statistics | en_US |
| ndsu.program | Statistics | en_US |
| ndsu.advisor | Magel, Rhonda |