> > G'day > > I just tried to introduce a naive user to R via doing a t-test on her > data using Rcmdr on OS X. Now I'm not sure if this is the right > mailing > list but I must say that the introduction was a complete and total > failure because of the OSX data editor that is called by Rcmdr. I > think > this is the one that comes with the R GUI. We tried to enter her data > into R and I couldn't do it using the OS X data editor. When I had > to go > to the command line she was clearly initialy put off by the poor > editor > and by the need for the command line to fix it. As she said, "how > can I > trust a stats program with my important data if they can't get data > entry working?". She promptly went back to Instat
> I know that the criticism she voiced isn't valid and that some > learning > is required for any program, but I think she has a point. The data > editor as it stands is a failure. The idea that you can add a column > but > not change the variable name and that you have to double click on each > cell to enter data is crazy. It is simply a pretty looking window with > less functionality than the old x11 interface. > Yes, the data editor is not that useful, and I be surprised if anyone uses it much at all. > I'm aware that the current model is "prepare your data elsewhere and > import it into R" but this is an absurd stance. Why is this an absurd stance? Entering a small data set like the one you describe can be done in TextEdit or any other text editor: "Variable1", "Variable2" x1, y1 x2, y2 ... ... Or, if you must have a spreadsheet, you can use OpenOffice and save to .csv. > It works for large data > sets that statistical experts deal with but then the casual t-test > requires several programs and an import step. A silly approach > especially when the data sets are small (about 10-20 entries) and all > the user wants to do is a simple t-test. > If braoder adoption of R is an aim then the OS X data editor needs > to be > at least as functional as the X11 one. The ability to double click to > change variable names and right click to change the variable type (or > menu entries to do this) is important if not essential. The ability to > tab to the next data entry slot is also a simple but important > function > that needs to be included. Right now it is a barrier to new OS X > users > who want to try out R using a simple t-test on a small data set. > > This is probably true. At the end of the day R is a command driven program. The Rcmdr GUI is an important learning tool, but it was never designed to replace the command line. I hated this at first, being trained as I was on SPSS, but in the long run I suspect you're going to be better off if you give up on R as a GUI driven tool. This is not to say that the Rcmdr interface is not useful: it is very useful, but primarily as a teaching tool (i.e., a way to learn R commands). > > From: "Peter Cowan" <[EMAIL PROTECTED]> > Date: March 11, 2008 1:18:20 AM EDT > To: [email protected] > Subject: Re: [R-SIG-Mac] OSX R Gui Data editor > > > John, > > I think you may be mixing up the R package Rcmdr [^1] with the Mac OS > X R gui. I've haven't used Rcmdr in years so I cannot comment on your > issue, but I think you were commenting on the Mac gui. > He clearly stated he was using the OS X data editor, called from Rcmdr. > <snip> > > If your colleague isn't interesting in learning to use a command line > program, then I suspect that R is not the correct choice for her. > Yes, exactly, although I agree this can be a problem because it scares people off. > > From: "Byron Ellis" <[EMAIL PROTECTED]> > Date: March 11, 2008 2:59:36 AM EDT > To: [EMAIL PROTECTED] > Cc: [email protected] > Subject: Re: [R-SIG-Mac] OSX R Gui Data editor > > > Your colleague's reaction is completely correct. If all you need to do > is hand enter 20 data points and run a t-test then even Instat is > probably overkill and R is definitely overkill. > <snip> I strongly disagree with this sentiment. I started using R as a calculator believe it or not. R is very good for simple as well as complex statistics. > Think of R like a big industrial > CNC mill or something. It's big, clunky and kind of a pain, but if you > need to make a set of intricate wheel rims to very high tolerances > there is nothing on this earth that can match it. However, not so > great for paper snowflakes, unless you've been using it forever in > which case its mostly out of habit... and you've lost your scissors. Again, I think this is just wrong. Doing simple t-tests in R is easy once you get used to the program. What exactly is so "big and clunky" about R? <snip> Ista [[alternative HTML version deleted]] _______________________________________________ R-SIG-Mac mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-mac
