In a question posted Oct-14-2007 to Yahoo! Answers, user lifetimestudentofmath asked:
How would you run this regression?
A relationship between beer expenditure and income was tested. The relationship may be qualitatively effected by gender. How would you test the hypothesis that women spend less money on beer than women?
My guess is that this is a homework question, and that the teacher wants students to use a dummy variable to represent gender, so that a simple interpretation of gender's coefficient will reveal the answer.
In reality, of course, the interaction of income and gender may yield a more nuanced answer. What if two regressions were performed, one for men and the other for women, with income as the predictor and beer expenditure as the target, and the regression lines crossed? Such a result precludes so simple a response as "men spend more on beer".
This question suggests another reason so many people hate statistics: its subtlety. The annoying thing about reality (which is the subject of statistical study), is that it is so complicated. Even things which seem simple will often reveal surprisingly complex behavior. The problem is that people don't want complicated answers. Although my response is: It is foolish to expect simple solutions to complicated problems, the fundamental, irreducible complexity of reality- which is mirrored in statistics- also drives negative feelings toward statistics.