search for: ymean

I need some help for a curious question of a friend of mine. She usually does some experiments (3-5 repeats for each exp) and then she calculates mean and standard deviation. In microsoft excel she writes something like the following sample mean sd a 1.25 0.35 b 2.65 0.65 c 3.45 0.50 She can do a vertical barplot graph just giving mean value and specifying the

Dear all, I would like to fit a linear regression with replication (on each year, observation is replicated, e.g 4 times). The independent variable ranges for instance 1-5 year, so I expect to have a linear fit of 5 points. For that purpose I do these (with dummy variables x and y): x<-rep(seq(1:5),4) y<-rnorm(20) linreg<-lm(y~x) fitted.values(linreg) # why produce 20 points of

Dear all: I am comparing the PLS outputs of R and SAS for the following data set: Y x1 x2 x3 3 6 2 2 3 1 5 5 4 7 4 1 5 6 5 6 2 4 3 2 8 5 0 9 where Y is the dependent variable and x1, x2, x3 are the independent variables. I found several PLS algorithms in R (NIPALS,SIMPLS,KERNEL PLS). SAS has SIMPLS and NIPALS. The following are the NIPALS calculations of

I have 4000 observations that I need to randomly relabel 1000 times and then calculate the mean of the 1000 values at each of the 4000 points. Any ideas for where to begin? Thanks Kevin -- View this message in context: http://r.789695.n4.nabble.com/Random-Relabelling-tp3463100p3463100.html Sent from the R help mailing list archive at Nabble.com.

...e info traceback() 5: inherits(unit, "unit") 4: is.unit(y) 3: textGrob(label = label, x = x, y = y, just = just, hjust = hjust, vjust = vjust, rot = rot, check.overlap = check.overlap, default.units = default.units, name = name, gp = gp, vp = vp) 2: grid.text(main, y = un(ymean + xlim[2] + xrange/10), gp = gpar(cex = 1, font = 2)) 1: plotpc.svd(x, pccenter = TRUE, pcscale = FALSE) -->%--- I am bit lost now about where I should continue looking for required modifications in the code. Any hints? Thanks in advance, Nikos

Hello all, I am a 2 month newbie to R and am stumped. I have a data set that I've run multivariate stats on using the manova function (I included the data set). Now it comes time for a table of effect sizes with significance. The univariate tests are easy. Where I run into trouble filling in the table of effect sizes is the Mahalanobis D as an effect size. I've included the table so

Hi, I want to plot grouped bars to compare 95% confidence interval estimates from two models. Each bar represents a 95% confidence interval estimate of a coefficient from one of the two models. Each group represents confidence interval estimates of the same coefficient from the two models. I think such a bar plot will nicely present whether 95% confidence interval estimates of the same