Intro To Statistical Tools For Data Mining Training 

Course Overview

Many improvement projects are 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. Very little prior knowledge of statistics is needed for this course. The 3-day course takes a very hands-on approach to learning. Participants will learn how to apply the methods via a combination of lecture and working examples using software that runs in Excel. The instructor will make time for one-on-one consulting so participants are encouraged to bring their own data sets to class.

Course Outline

Introduction to data mining
Exploring and preparing data
Introduction to modeling and validation
Multiple linear regression
Logistic regression
Discriminant analysis
Model validation
Neural networks
Classification and regression trees
Combining models (bagging and boosting)
Cluster analysis
Association rules

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