Last time we created two variables and used the lm() command to perform a least squares regression on them, and diagnosing our regression using the plot() command.
Just as we did last time, we perform the regression using lm(). This time we store it as an object M. (more…)
I am reviewing your notes from your workshop on assumptions. You have made it very clear how to analyze normality for regressions, but I could not find how to determine normality for ANOVAs. Do I check for normality for each independent variable separately? Where do I get the residuals? What plots do I run? Thank you!
I received this great question this morning from a past participant in my Assumptions of Linear Models workshop.
It’s one of those quick questions without a quick answer. Or rather, without a quick and useful answer. The quick answer is:
Do it exactly the same way. All of it.
The longer, useful answer is this: (more…)
Here’s a little reminder for those of you checking assumptions in regression and ANOVA:
The assumptions of normality and homogeneity of variance for linear models are not about Y, the dependent variable. (If you think I’m either stupid, crazy, or just plain nit-picking, read on. This distinction really is important). (more…)