Dating age difference rule of thumb
This section should help the user to understand the rough differences in the techniques and at least enough information to be dangerous and well armed enough to not be baffled by the vendors of different data mining tools.
The main techniques that we will discuss here are the ones that are used 99.9% of the time on existing business problems.
They were being used long before the term data mining was coined to apply to business applications.
However, statistical techniques are driven by the data and are used to discover patterns and build predictive models.
Knowing statistics in your everyday life will help the average business person make better decisions by allowing them to figure out risk and uncertainty when all the facts either arent known or cant be collected.
Even with all the data stored in the largest of data warehouses business decisions still just become more informed guesses.
This is certainly more true today than it was when the basic ideas of probability and statistics were being formulated and refined early this century.
Thus this section contains descriptions of techniques that have classically been used for decades the next section represents techniques that have only been widely used since the early 1980s.
There are certainly many other ones as well as proprietary techniques from particular vendors - but in general the industry is converging to those techniques that work consistently and are understandable and explainable.
By strict definition "statistics" or statistical techniques are not data mining.
He explained to me that they not only now were storing the information on the flies but also were doing "data mining" adding as an aside "which seems to be very important these days whatever that is".
I mentioned that I had written a book on the subject and he was interested in knowing what the difference was between "data mining" and statistics. The techniques used in data mining, when successful, are successful for precisely the same reasons that statistical techniques are successful (e.g.