Introduction
Daniel P. McGibney
Additional contact information
Daniel P. McGibney: University of Miami, Management Science
Chapter Chapter 1 in Applied Linear Regression for Business Analytics with Python, 2026, pp 1-8 from Springer
Abstract:
Abstract In today’s data-driven world, businesses rely on regression analysis to make informed decisions. It supports a wide range of applications, from setting competitive prices to crafting effective marketing campaigns. Business analytics represents the broader framework within which regression operates, combining statistical modeling with computational methods to transform data into strategic insight.
Date: 2026
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:isochp:978-3-032-23806-1_1
Ordering information: This item can be ordered from
http://www.springer.com/9783032238061
DOI: 10.1007/978-3-032-23806-1_1
Access Statistics for this chapter
More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().