search for: oknyya1ld

.... I read quite a lot about outlier removal already and I think the most common technique for that seems to be Principal Component Analysis (PCA). However, I think that these technqiue is quite subjective. When is an outlier an outlier? I uploaded an example PCA plot here: http://s14.postimage.org/oknyya1ld/pca.png Should we treat the green and red dots as outliers already or only the blue one which lies outside the 95% confidence interval. It seems very arbitrary how people remove outliers using PCA. I also thought about fitting a linear model through my data and look at distribution of the residua...