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I'm working with a linear model with four factors as explicatory variables, being all of them significally (e.g. y ~ a + b + c + d). I thought that the residuals of a linear model keep the variance not explained by the model, so if I use my model with just three factors (y ~ a + b + c) and keep the residuals is expected that in a new model with the residuals as dependent variable and the four factor as independent (residuals ~ d) that factor (d) will be si...

...ol speed and the tool type ( type A, Type B , Type C) where the response is the tool speed and the regressor is the tool type. I introduced two dummy variables X1 and X2 as follows X1 X2 Tool A 0 0 Tool B 0 1 Tool C 1 0 Model<-Lm (y~X1+X2) My question is on the residual plot, it looks like three cluster because I have three tool types. Is such a plot is ok with the constant variance assumption and normality (below is a link for the plot)?I have never seen such a plot of the residuals http://www.nabble.com/file/p22972254/question.JPG question.JPG -- View this...