Skip to main content

The Use of Multivariate Analysis Techniques

  • Chapter
Data Mining for Managers
  • 760 Accesses

Abstract

The most commonly used techniques in predictive modeling are linear and logistic regression. The statistics in linear regression predict outcomes with a continuous range of values; logistic regression predicts outcomes that are categorical in nature. The most commonly used logistic routines are used to predict yes/no behaviors, such as response, attrition, or credit default. The outcome derived can also be a set of rules such as CHAID rather than a score, which is the predicted outcome of either logistic or linear regression.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Authors

Copyright information

© 2014 Richard Boire

About this chapter

Cite this chapter

Boire, R. (2014). The Use of Multivariate Analysis Techniques. In: Data Mining for Managers. Palgrave Macmillan, New York. https://doi.org/10.1057/9781137406194_15

Download citation

Publish with us

Policies and ethics