> Thanks for the example, Hadley. To me, this suggests we should stop > teaching histograms in Stat 101 and instead use quantile plots, which > give excellent results for n=100 and even surprisingly good results > for n=10:
It all depends on what you're trying to do - I don't think histograms are particularly good as density estimators, but that's not what you're using them for most of the time! You're using them as an exploratory tool to try and understand what's going on in your data - often you'll need to use very small bin widths which help find unexpected gaps and patterns in your data. It's helpful to have some feel for what common distributions look like. Hadley -- http://had.co.nz/ ______________________________________________ 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.
