On 08/03/2009 10:49 AM, hadley wickham wrote:
More seriously : I don't think relative numbers of package downloads can be interpreted in any reasonable way, because reasons for package download have a very wide range from curiosity ("what's this ?"), fun (think "fortunes"...), to vital need tthink lme4 if/when a consensus on denominator DFs can be reached :-)...). What can you infer in good faith from such a mess ?So when we have messy data with measurement error, we should just give up? Doesn't sound very statistical! ;)
I think the situation is worse than messy. If a client comes in with data that doesn't address the question they're interested in, I think they are better served to be told that, than to be given an answer that is not actually valid. They should also be told how to design a study that actually does address their question.
You (and others) have mentioned Google Analytics as a possible way to address the quality of data; that's helpful. But analyzing bad data will just give bad conclusions.
Duncan Murdoch ______________________________________________ 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.
