The dummy variable trap
{"Image DocumentName": "The dummy variable trap", "Image ImageDescription": "Suppose you have a set of multiple binary (dummy) variables, which are mutually exclusive and exhaustive \u2013 that is, there are multiple categories and every observation falls in one and only one category (Freshmen, Sophomores, Juniors, Seniors, Other). If you include all these dummy variables and a constant, you will have perfect multicollinearity \u2013 this is sometimes called the dummy variable trap. Why is there perfect multicollinearity here? Solutions to the dummy variable trap: Omit one of the groups (e.g. Senior), or. Omit the intercept. What are the implications of (1) or (2) for the interpretation of the coefficients?", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}