```Date: Fri, 13 Jul 2007 05:42:15 -0400 Reply-To: Peter Flom Sender: "SAS(r) Discussion" From: Peter Flom Subject: Re: Regression Skewed data! Comments: To: Pooch Content-Type: text/plain; charset=UTF-8 Pooch wrote >I have a data where both my dependent and independent variables are >left-skewed. What transformation do I use to normalize both of them >and use them in regression? > First, ordinary least squares regression does not assume a particular distribution for either the dependent or independent variables, it assumes that the *residuals* are normally distributed. So, run the regular regression and look at them If the residuals are not normally distributed, then transformations are *one* option. But not the only one, and perhaps not the best one. There are other regression models that may be better (e.g. robust regressions). Some of this is a matter of preference, but some is not. Should you transform? Well, does the transformation make substantive sense? Some people use the Box-Cox method to come up with a good transformation, but raising a variable to a fractional power usually does not lead to easy interpretation. Also, transforming to normalize the residuals may cause other problems (e.g. heteroskedasticity). I suggest you write back to SAS-L and list 1) What your DV and IVs are 2) What you are trying to figure out 3) How many IVs, how many N, and so on 4) What the residuals from OLS regression look like Then someone may be able to provide you with more guidance Peter ```

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