Introduction to Statistical Tools Used for Data Mining

Many projects can be very data intensive and the statistical tools taught in traditional college curricula are often inadequate for solving the problem at hand. While there are many aspects and definitions of data mining, the basic idea is to find patterns in data sets. Although marketed for large databases, the techniques are applicable to any size data set. While data management is an important subject, this course will focus on the statistical models used in data mining. It will cover the most useful tools such as linear regression, logistic regression, classification trees, discriminate analysis, neural networks, clustering, nearest neighbors, bump hunting, and market basket analysis. While these data mining tools may sound exotic and difficult to understand, they are actually fairly straightforward and modern software makes it easy to use them. This is a color version for AAA.