search for: block3

...ment7 -0.59955 0.54247 -1.105 0.270371 treatment8 0.80747 0.85639 0.943 0.346863 treatment9 0.10081 0.54320 0.186 0.852954 treatment10 0.43933 0.53421 0.822 0.411823 block2 -1.87242 0.66448 -2.818 0.005312 ** block3 0.10927 0.22670 0.482 0.630328 block4 -1.45648 3.71684 -0.392 0.695574 block5 0.25447 0.22033 1.155 0.249475 block6 -0.32177 0.22269 -1.445 0.150021 treatment1:block2 -0.38808 0.26398 -1.470 0.143073 t...

...- brick0 mirror0 replicate block1 - brick1 mirror1 distribute unify - block0 block1 or server sdb1 sdb2 xen0 brick0 mirror3 xen1 brick1 mirror0 xen2 brick2 mirror1 xen3 brick3 mirror2 replicate block0 - brick0 mirror0 replicate block1 - brick1 mirror1 replicate block2 - brick2 mirror2 replicate block3 - brick3 mirror3 distribute unify - block 1 block2 block3 block4 ><> Nathan Stratton CTO, BlinkMind, Inc. nathan at robotics.net nathan at blinkmind.com http://www.robotics.net http://www.blinkmind.com

...## Using lm npk.lm <- lm(model, npk) ( s.npk.lm <- summary(npk.lm) ) ... Estimate Std. Error t value Pr(>|t|) (Intercept) 54.8750 0.8021 68.415 < 2e-16 *** block1 1.7125 1.3893 1.233 0.24131 block2 1.6792 0.8021 2.093 0.05822 . block3 -1.8229 0.5672 -3.214 0.00744 ** ... s.npk.lm$coef["block1","Pr(>|t|)"] # this works [1] 0.2413061 ## Using aov npk.aov <- aov(model, npk) ( s.npk.aov <- summary(npk.aov) ) ... Df Sum Sq Mean Sq F value Pr(>F) block 5 343.29...

...median foreground =values of x-variables fg1=as.matrix(new[,9]) length(fg1) mean(fg1) # calculate the mean of x1 #### I try to do something like :########## block1=fg1[layout$Block==1,] block2=fg1[layout$Block==1,] block2=fg1[layout$Block==1,] average=(block1+block2+block3)/3 but it did not work. ################## How can i calculate the means of remaining x_variables? ######### Read data for the remaining slides =x2,x3,x4,x5 ########### for (i in 2:num.slides){ na1 <- strsplit(na[[i]][k],".txt") na2 <- strsplit(na1[[1]][1]...

...2.1460 0.168648 P:K 1 0.48 0.48 0.0312 0.862752 Residuals 12 185.29 15.44 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 > coefficients(npk.aov) (Intercept) block2 block3 block4 block5 block6 51.8250000 3.4250000 6.7500000 -3.9000000 -3.5000000 2.3250000 N1 P1 K1 N1:P1 N1:K1 P1:K1 9.8500000 0.4166667 -1.9166667 -3.7666667 -4.7000000 0.5666667 The output for the ANOVA table is exactly the...

...test output; --- /Users/cartman/Sources/rsync/testtmp/devices/rsync.chk 2010-09-07 15:17:06.000000000 +0300 +++ /Users/cartman/Sources/rsync/testtmp/devices/rsync.out 2010-09-07 15:17:06.000000000 +0300 @@ -1,6 +1,7 @@ .d..t...... ./ cDc.t...... block cDc........ block2 +cD+++++++++ block3 cD+++++++++ char cD+++++++++ char2 cD+++++++++ char3 test 4 failed ----- devices log ends -- Configure bugmail: https://bugzilla.samba.org/userprefs.cgi?tab=email ------- You are receiving this mail because: ------- You are the QA contact for the bug, or are watching the QA contact.

On Tue, 14 Jul 2015 08:59:25 +0200, Paul Slootman wrote: > btrfs has support for this: you make a backup, then create a btrfs > snapshot of the filesystem (or directory), then the next time you make a > new backup with rsync, use --inplace so that just changed parts of the > file are written to the same blocks and btrfs will take care of the > copy-on-write part. That's

...39; 0.01 `*' 0.05 `.' 0.1 ` ' 1 > model.tables(balanced,"means") Tables of means Grand mean 14.41667 blocks 1 2 3 4 13.667 16.333 12.333 15.333 trtmnts 1 2 3 10.50 13.75 19.00 Entering the data again and dropping treatment 2, block3 and treatment 3, block 4, we have: > blocks2<-factor(c(1,2,3,4,1,2,4,1,2,3)) > trtmts2<-factor(c(1,1,1,1,2,2,2,3,3,3,)) > data2<-c(10,12,9,11,13,15,16,18,22,17) > unbalanced<-aov(data2~blocks2+trtmts2) > summary(unbalanced) Df Sum Sq Mean Sq F value Pr(&...

mainly question for the intel folks, any chance to rerun the ltp testsuites to see how we are doing these days with all the changes ? thanks :) Wim