On Wed, 22 Oct 2003 11:51:46 +0100 (BST), you wrote: >Without knowing the seed used it is impossible for us to reproduce this, >but I am not seeing anything strange.
I'm getting strange results in 1.8.0 for Windows too. > set.seed(1) > x <- rnorm(50) > y <- rnorm(50) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 23640, p-value = 1 alternative hypothesis: true rho is not equal to 0 sample estimates: rho -0.1351741 > x <- rnorm(50) > y <- rnorm(50) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 17248, p-value = < 2.2e-16 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.1717647 > x [1] -0.62036668 0.04211587 -0.91092165 0.15802877 -0.65458464 1.76728727 [7] 0.71670748 0.91017423 0.38418536 1.68217608 -0.63573645 -0.46164473 [13] 1.43228224 -0.65069635 -0.20738074 -0.39280793 -0.31999287 -0.27911330 [19] 0.49418833 -0.17733048 -0.50595746 1.34303883 -0.21457941 -0.17955653 [25] -0.10019074 0.71266631 -0.07356440 -0.03763417 -0.68166048 -0.32427027 [31] 0.06016044 -0.58889449 0.53149619 -1.51839408 0.30655786 -1.53644982 [37] -0.30097613 -0.52827990 -0.65209478 -0.05689678 -1.91435943 1.17658331 [43] -1.66497244 -0.46353040 -1.11592011 -0.75081900 2.08716655 0.01739562 [49] -1.28630053 -1.64060553 > y [1] 0.45018710 -0.01855983 -0.31806837 -0.92936215 -1.48746031 -1.07519230 [7] 1.00002880 -0.62126669 -1.38442685 1.86929062 0.42510038 -0.23864710 [13] 1.05848305 0.88642265 -0.61924305 2.20610246 -0.25502703 -1.42449465 [19] -0.14439960 0.20753834 2.30797840 0.10580237 0.45699881 -0.07715294 [25] -0.33400084 -0.03472603 0.78763961 2.07524501 1.02739244 1.20790840 [31] -1.23132342 0.98389557 0.21992480 -1.46725003 0.52102274 -0.15875460 [37] 1.46458731 -0.76608200 -0.43021175 -0.92610950 -0.17710396 0.40201178 [43] -0.73174817 0.83037317 -1.20808279 -1.04798441 1.44115771 -1.01584747 [49] 0.41197471 -0.38107605 In 1.7.1, the same code gives the same x and y and rho values, but more reasonable p-values: > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 23640, p-value = 0.3482 alternative hypothesis: true rho is not equal to 0 sample estimates: rho -0.1351741 > x <- rnorm(50) > y <- rnorm(50) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 17248, p-value = 0.2322 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.1717647 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-devel