of AT&T Bell Laboratories and I worked on. There is a window with a cyclic graph in it. As Paul Velleman pointed out this morning, it has an entry point, but no exit. This represents the process of data analysis. It is never finished. But you can exit at any point you want. There is no specified plan of things that must be done before you can quit. But when you do exit, the system would suggest a thing to do.
For example, the grayed-in box is suggesting that the first thing to do is to select the data. When that has been done, a sub-strategy might be given, a recursive definition of a strategy. A new strategy box opens up that focuses both on variables and observations or cases. When that is finished, that box closes.
Then the user goes to the next set of possible things that the strategy would suggest, either describing the data, transforming the data, or defining a model. As the flow indicates, if you describe the data, you still can again transform data or define the model, and conversely for transforming. But once you have a model defined, the only thing the strategies then suggest you do is to fit the model. Fitting the model itself is recursively defined. Within that one would see a more involved strategy depicting what to do.
This is one possible way of guiding a data analysis. Where does this strategy graph come from? It comes from an expert. Somewhere, an expert at multiple regression must have sat down and created this graph. In fact, this graph was created by Lubinsky and me after looking at the book by Daniel and Wood , where such a strategy for doing multiple regression appears on the inside front cover. There are also analogous graphs presented for principal components in a factor analysis, for example. Such sources for