Hi, I am a consultant in Quality Management. I am exploring the use of R with any GUI - R commander/Rkward for doing analytical work. Have installed R, R Commander and Rkward.
I hope to learn by doing various exercises that I use for teaching analytical techniques to my clients. I would be posting the data on this mailing list, and the rkward mailing list wherever I get stuck. First such technique I am trying to explore is the use of boxplots. The data is pasted below: Season Transporter Distance Tonnage Time 1 1 500 1 17 1 1 500 2 22 1 1 1000 1 23 1 1 1000 2 29 1 1 1500 1 33 1 1 1500 2 38 1 2 500 1 19 1 2 500 2 26 1 2 1000 1 30 1 2 1000 2 35 1 2 1500 1 42 1 2 1500 2 42 2 1 500 1 18 2 1 500 2 24 2 1 1000 1 25 2 1 1000 2 26 2 1 1500 1 35 2 1 1500 2 38 2 2 500 1 21 2 2 500 2 24 2 2 1000 1 28 2 2 1000 2 37 2 2 1500 1 36 2 2 1500 2 44 In this exercise, I am trying to plot box plots of the variable "Time", the last column and separated by all the other variables- Season, Transporter, Distance and Tonnage. I expect the output in form of multiple box plots, arranged side by side so that I can compare the time performance for, say, season 1, transporter 2, Distance 500 and tonnage 2 with, say, season 2, transporter 1, Distance 500 and tonnage 2. The box plot command in R Commander (Grpahs->Boxplot...) has a button called "plot by groups" presumably to achieve what I am trying to do. However, on clicking I don't get any further output. What am I missing? (There is nothing equivalent to this button under Rkward) I tried to search the mailing list on box plot, but could not find anything relevant. I have also searched in manual and seen this type (or even more complex analysis) being done on terminal. However, I need to do it under (any) GUI. Any help is highly appreciated. Thanks Vikas Garud ______________________________________________ R-help@r-project.org 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.
