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...t;) curve(dnorm(x,mean=mean(xbar),sd=sd(xbar)),add=TRUE,lwd=2,col="red") The problem is that I am getting greater than 1 probabilities in the Y axis? Is there a way to correct this? Many thanks in advance. Joao -- View this message in context: http://r.789695.n4.nabble.com/Probabilities-greather-than-1-in-HIST-tp3333388p3333388.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

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I'm trying to do something very simple... I wan to plot a histogram where the y axis represent the percentage of the total sample that each bin represents. I know how to plot a histogram with the counts and density... but can't find anything that gives me perenct of sample on the y axis. Any help is appriciated Below is the script I'm working with par(mfrow=c(1,2))

Hi R developers: Congratulations for the new R 2.10.0 version. It is a huge effort! Thank you for your work and dedication. I just want to ask how to make this "strip blank" function to work again (it works on R.2.9.2). alumnos$AL_NUME_ID<-sub("(^ +)|( +$)","",alumnos$AL_NUME_ID),) "alumnos" is a data base with 900.000 rows and 72 columns. and

This patch modifies the physinfo hcall to export NUMA CPU and Memory topology information. The new physinfo hcall is integrated into libxc and xend (xm info specifically). Included in this patch is a minor tweak to xm-test''s xm info testcase. The new fields in xm info are: nr_nodes : 4 mem_chunks : node0:0x0000000000000000-0x0000000190000000

...are two variances data: flat_550_W_realism and flat_550_W_realism_AH F = 0.7486, num df = 14, denom df = 13, p-value = 0.597 alternative hypothesis: true ratio of variances is not equal to 1 95 percent confidence interval: 0.2428979 2.2546308 sample estimates: ratio of variances 0.7485758 p-value greather than 0.05 so in the t-test I put the option var.equal=TRUE: > t.test(flat_550_W_realism,flat_550_W_realism_AH, var.equal=TRUE) Two Sample t-test data: flat_550_W_realism and flat_550_W_realism_AH t = -2.2361, df = 27, p-value = 0.03381 alternative hypothesis: true difference in means is not e...

Dear all, I would like to know which is the right way to check the normality assumption for performing ANOVA. How do you check normality for the following example? I did an experiment where people had to evaluate on a 7 point scale, the degree of realism of some stimuli presented in 2 conditions. The problem is that if I check normality with the Shapiro test I get that the data are not