similar to: Choice of notch size in R

Dear list members, Can anyone tell me how the notches in boxplot(Y~X,notch=T) are calculated? What do these notches represent exactly? I?d suppose they are Conficence Intervals for the median, but I?ve also been told they might show Least Significant Difference (LSD) equivalents. I would very much appreciate any help from you. Best regards Chris.

Hi I'm getting a weird result when I try to switch from a normal box plot to a notched one. The ends of the box fold down toward the median giving a horned appearance. Is just the sample itself? It is small, but the un-notched plot looks okay. Anyway to fix this? e7=as.vector(c(234,37,98,116,47)) boxplot(e7, plot=TRUE, notch=TRUE) Thanks very much.

A function I've been using for a while returned a surprising [to me, given the data] error recently: Error in plot.window(xlim, ylim, log, asp, ...) : Logarithmic axis must have positive limits After some digging I realized what was going on: x <- c(10460.97, 10808.67, 29499.98, 1, 35818.62, 48535.59, 1, 1, 42512.1, 1627.39, 1, 7571.06, 21479.69, 25, 1, 16143.85, 12736.96,

Another naive stats question. I'm trying to better understand what boxplots are telling me. I think what I see is the median and the boundaries of the 1st and 3rd quartiles. The whiskers represent the range of the data unless there are points which are outside "range" (default: 1.5) times the distance from the median to that quartile. Is that right? I've read the

Good Afternoon- I was wanting to alter the boxplot to remove the lower whisker, both the whisker line and staple just on the lower end. Is there a way to do this? As my code is currently: boxplot(log_loads~ind,data=nfmaum, horizontal=TRUE, notch=T, outline=FALSE, whisker=0, main="Maumee River Near Future Climate Scenarios", ylab="Log Load",xlab="Climate Scenarios")

How are the lower/upper whiskers defined in the default version of boxplot {graphics}? I tried help(boxplot) and searching www.rseek.org, but I was unable to determine an absolute answer. I checked out the definition of boxplot according to Wikipedia (http://en.wikipedia.org/wiki/Box_plot), but it also had several approaches listed for how the whiskers could be determined, so I'm just

I really like the ease of use with the boxplot command in R. I would rather have a boxplot that shows the average value and the standard deviation then the median value and the quartiles. Is there a way to do this? Chad Junkermeier, Graduate Student Dept. of Physics West Virginia University PO Box 6315 210 Hodges Hall Morgantown WV 26506-6315 phone: (304) 293-3442 ext. 1430 fax: (304)

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

Hi all, I'm just getting started with R and I would appreciate some help. I'm having trouble creating a boxplot with whiskers at the 95th and 5th percentiles instead of at 1.5 * IQR. I have read the relevant documentation, and checked existing mails on this topic. I found a small modification that should work : https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried to

Sorry to repost this, but it looks like it's getting buried in r-help (originally posted October 5: my experience says that if it hasn't been answered by then it won't be). I wouldn't bother, but I'm worried that r-devel might be better, *and* a previous e-mail of mine on the subject in January also seemed to get buried. Synopsis: boxplot notches look weird when notches are

Dear R-list, In the R-book, p.464, Michael Crawley recommends that error bars for bar plots of normally distributed continuous response variables with categorical explanatory variables be given by 1/2 of the least significant difference, where the least significant difference is defines as qt(0.975,degrees_of_freedom)*standard_error_of_the_difference. The idea is that the above quantity

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at

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dear all, could somebody tell me how I can plot mild outliers as a circle(?) and extreme outliers as an asterisk(*) in a box-whisker plot? Thanks very much in advance -- View this message in context: http://www.nabble.com/mild-and-extreme-outliers-in-boxplot-tp25040545p25040545.html Sent from the R help mailing list archive at Nabble.com.

Was there ever a convenient method provided to add boxplots to the current plot at specified x values? There was a question by Martin Maechler some time ago here, but I could seem to find any satisfactory resolution of it. I see that there is an add=T option to boxplot and bxp, but I don't see how to set the x-values. url: http://www.econ.uiuc.edu Roger Koenker email roger at

I'm graphing a series of boxplots of grouped data inside a function that passes the data.frame, the names vector, and a title vector. Because both the data subset changes with each successive pass through the function, occasionally the names vector turns up with only one group to plot. This is an expected result. However, when the names argument in boxplot has only a single name, it

Hello, I know this has been covered on here before, but as a complete novice, I need a little more guidance. I would like to produce boxplots with the whiskers extending to the 10 and 90th percentiles. I found this code: myboxplot.stats <- function (x, coef = NULL, do.conf = TRUE, do.out = TRUE) { nna <- !is.na(x) n <- sum(nna) stats <- quantile(x, c(.1,.25,.5,.75,.9), na.rm

Dear all, I am a total beginner in R, so sorry if this is the wrong place. I am using R 2.10.1 on a Mac (Mac OS 10.6.2). I have this small dataset : growth sugar 75 C 72 C 73 C 61 F 67 F 64 F 62 S 63 S I have no problem reading the table, or getting the summary, but if I try boxplot(growth~sugar, ylab="growth", xlab="sugar", data=Dataset), I have the following error :

Hello R-Help, Could anybody tell me how the boxplot-function calculates the upper and lower extremes of the notch contained in $conf which I assume is the confidence interval? Is it reliable for data which is not normally distributed? If not, how can I calculate and boxplot a specific confidence interval for not normally distributed data in R (increasing the sample size does not normalize the

R helpers I am getting to grips with R but came across a small problem today that I could not fix by myself. I have 3 text files, each with a single column of data. I read them in using: myData1<-scan("C:/Program Files/R/myData1.txt") myData2<-scan("C:/Program Files/R/myData2.txt") myData3<-scan("C:/Program Files/R/myData3.txt") I wanted to produce a