Hey R-Comunity,
I'd like to print out an histogram of some experimental data and add a smooth curve of a normal distribution with an ideally generated population having the same mean and standard deviation like the experimental data. The experimental data is set as vector x and its name is set to group.name. I paint the histogram as follows: hist(data, freq=FALSE, col="lightgrey", ylab="Density", xlab=group.name) First I did the normal distribution curve this way: lines(x, dnorm(x, mean=mean(x), sd=sd(x)), type="l", lwd=2) This curve just uses as many values as there are in x. When using small amounts of sample populations the curve looks really shaky. I tried this one using a high level plot function as well: curve(dnorm, n=10000, add=TRUE, xlim=range(x)) The advantage is, now I can set an ideal population of 10000 to get the ideal curve really smooth. But the big disadvantage is, I don't know how to add "mean=mean(x), sd=sd(x)" arguments to it? It says that it can't mix high level with low level plot functions when I try to set some kind of parameter like "n=10000" to the low level function, it says that there ain't enough x values. So my question is, how to get a smooth curve placed of dnorm over an histogram of sample data, ideally by using the curve method? TIA, Lothar Rubusch ______________________________________________ R-help@stat.math.ethz.ch 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.