Simple Linear Regression

Daniel P. McGibney
Additional contact information
Daniel P. McGibney: University of Miami, Management Science

Chapter Chapter 4 in Applied Linear Regression for Business Analytics with Python, 2026, pp 73-112 from Springer

Abstract: Abstract Albert Einstein’s quote above stresses the paramount importance of simplicity. In regression analysis, focusing on only two variables illustrates the concepts in a clear and simple way. Thus, in Chap. 3 , we calculated the least squares line by using two variables. We also plotted scatter plots and calculated correlation coefficients to further assess the linear relationship. From this analysis, we obtained a detailed understanding of the relationship between two variables. Upon understanding a linear relationship, other more complicated processes become easier to grasp.

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_4

Ordering information: This item can be ordered from
http://www.springer.com/9783032238061

DOI: 10.1007/978-3-032-23806-1_4

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 ().