Hello, I've two data.frames (data1 and data4), dec="." and sep=";". http://r.789695.n4.nabble.com/file/n4199964/data1.txt data1.txt http://r.789695.n4.nabble.com/file/n4199964/data4.txt data4.txt
When I do plot(data1$nx,data1$ny, col="red") points(data4$nx,data4$ny, col="blue") , results seem very similar (at least to me) but the R-squared of summary(lm(data1$ny ~ data1$nx)) and summary(lm(data4$ny ~ data4$nx)) are very different (0.48 against 0.89). Could someone explain me the reason? To be complete, I am looking for an simple indicator telling me if it is worthwhile to keep the values provided by lm. I thought that R-squared could do the job. For me, if R-squared is far from 1, the data are not good enough to perform a linear fit. It seems that I'm wrong. Thanks for your explainations. Ptit Bleu. -- View this message in context: http://r.789695.n4.nabble.com/lm-and-R-squared-newbie-tp4199964p4199964.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
