How can we use statistics to get at causal impact? Of course, correlation does not imply causation. Remember my lesson from a Dilbert's comic last week. But still, there are inferences to be drawn somehow. It may be a fact that MacDonald's just spent a lot of money on an ad campaign involving firecrackers and tapdancing penguins. It may be, also, that they sold a million hamburgers worldwide yesterday. It does not follow that they sold the million hamburgers because of that ad campaign. What MacDonald's clearly wants is some idea of how many hamburgers they would have sold if they had had some other ad campaign in place, possibly some less expensive campaign. Something involving their familiar clown and his sidekicks. Here's a social sciency thing about "Bayesian structural time-series models" that aims at getting at the problem. It's actually based on the experiences of Google, paid clicks versus free clicks, etc. -- I just prefer the MacDonald...