Business Analytics

Chapter 4

Data Mining: Helping to Make Sense of Big Data

Barry Keating

Learning Objectives

After reading this chapter, one should be able to:

• Distinguish “data mining” from online transaction processing.
• Define data mining.
• Explain the four categories of tools available in data mining.
• Relate common data mining terminology to standard statistical terminology.
• Use R.A. Fisher’s linear classifier technique.
• Interpret the output from a k-Nearest-Neighbor model estimation.
• Use and explain the two most common diagnostic statistics in data mining.

Introduction*

One apocryphal story about the origin of statistics (and hence analytics in general) describes a tale going back to the 17th century in London. During the plague that decimated London and ...