I am sure I am opening myself up to looking stupid, but I have two samples with medians of 613.5 and 189 (difference in location of 424 compared to the difference suggested from the wilcoxon of 291.5)
> wilcox.test(pipwtCount,pipwdCount, conf.int=TRUE, na.rm=TRUE) Wilcoxon rank sum test data: pipwtCount and pipwdCount W = 822, p-value = 0.01227 alternative hypothesis: true location shift is not equal to 0 95 percent confidence interval: 58 639 sample estimates: difference in location 291.5 The data is here > pipwtCount [1] 532 298 215 1588 38 180 284 376 5349 1024 650 605 1307 6147 21 [16] 453 23 1983 1048 464 2183 1028 1361 163 175 5944 569 622 793 70 [31] 67 1188 248 3010 19 2179 1339 408 113 739 2615 4619 > pipwdCount [1] 89 384 12 703 2 138 189 383 314 482 96 907 90 1193 154 [16] 305 61 414 4764 1066 121 143 102 174 44 2896 NA 1103 161 199 > median(pipwtCount) [1] 613.5 > median(pipwdCount,na.rm=T) [1] 189 > 613.5-189 [1] 424.5 I would appreciate if someone could point out the obvious to me, and explain why there is such a large discrepancy in the differences in location. Many thanks, Graham [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.