EconPapers    
Economics at your fingertips  
 

Building Multiple Regression Models

Cynthia Fraser ()
Additional contact information
Cynthia Fraser: University of Virginia, McIntire School of Commerce

Chapter Chapter 11 in Business Statistics for Competitive Advantage with Excel 2019 and JMP, 2019, pp 253-291 from Springer

Abstract: Abstract Explanatory multiple regression models are used to accomplish two complementary goals: identification of key drivers of performance and prediction of performance under alternative scenarios. The variables selected affect both the explanatory accuracy and power of models, as well as forecasting precision. In this chapter, the focus is on variable selection, the first step in the process used to build powerful and accurate multiple regression models.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-20374-0_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030203740

DOI: 10.1007/978-3-030-20374-0_11

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-06-01
Handle: RePEc:spr:sprchp:978-3-030-20374-0_11