You've got to state the problem little bit more clear. What do you mean by "set"? Is it a list of certain possible values, available as outcomes of each single measurement (variate)? Or is it something else? How many variates do you have inside each sample? What is it exactly that you want to find?
Do you want just to compare sample #1 and #2? There seems to be not enough variates for reliable result. Still, you may want to look at central tendencies (mean, median), i.e. location shift of samples, homogeneity of their variances, or the overall shape of empirical distributions. If your data are NOT normally distributed, you may use Wilcoxon rank sum test for medians,Kolmogorov-Smirnov for comparing empirical distribution functions and median-centering Fligner-Killeen test for homogeneity of variances. Or may be you are in fact looking for something else? May be you suspect that variates inside each sample vary together, according to some outside force? In that case you may want to calculate correlation coefficient - Perason product-moment for normal and Spearman for NOT normal data. All in all it seems like you need to consult some statistical textbook = ) Socal and Rolf is a good choice setrofim wrote: > > I have a bunch of benchmark measurements that look something like this: > sample.1 0.0000066660 0.0000062500 0.0000058330 0.0000058330 > 0.0000058330 > ... > i.e each measurement take on one of a set of values. The set values isn't > fixed, but they seem to go up increments; in this case, it appears to be > about 4.17e-07 (e.g. it would be impossible for a measurement to be > 0.0000066440). > What is way to test for significant differences between two samples? > -- View this message in context: http://r.789695.n4.nabble.com/Significance-test-tp3836155p3836365.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.
