Linear Regression

Randall Schumacker and Sara Tomek
Additional contact information
Randall Schumacker: University of Alabama
Sara Tomek: University of Alabama

Chapter Chapter 13 in Understanding Statistics Using R, 2013, pp 219-228 from Springer

Abstract: Abstract In the late 1950s and early 1960s, the mathematics related to solving a set of simultaneous linear equations was introduced to the field of statistics. In 1961, Franklin A. Graybill published a definitive text on the subject, An Introduction to Linear Statistical Models, which piqued the curiosity of several scholars. A few years later in 1963, Robert A. Bottenberg and Joe H. Ward, Jr., who worked in the Aerospace Medical Division at Lackland Air Force Base in Houston, Texas, developed the linear regression technique using basic algebra and the Pearson correlation coefficient. Norman R. Draper and Harry Smith, Jr. in 1966 published one of the first books on the topic, Applied Regression Analysis. In 1967, under a funded project by the U.S. Department of Health, Education, and Welfare, W. L. Bashaw and Warren G. Findley invited several scholars to the University of Georgia for a symposium on the general linear model approach to the analysis of experimental data in educational research. The five invited speakers were: Franklin A. Graybill, Joe H. Ward, Jr., Ben J. Winer, Rolf E. Bargmann, and R. Darrell Bock. Dr. Graybill presented the theory behind statistics, Dr. Ward presented the regression models, Dr. Winer discussed the relationship between the general linear regression model and the analysis of variance, Dr. Bargmann presented applied examples which involved interaction and random effects, and Dr. Bock critiqued the concerns of the others and discussed computer programs that would compute the general linear model and analysis of variance. Since the 1960s, numerous textbooks and articles in professional journals have painstakingly demonstrated that the linear regression technique, presented by Bottenberg and Ward, is the same as the analysis of variance. In recent years, multiple regression techniques have proven to be more versatile than analysis of variance in handling nominal and ordinal data, interaction effects, and non-linear effects.

Keywords: Bottenberg; Aerospace Medical Division; General Linear Model Approach; True Regression Equation; Math Achievement Scores (search for similar items in EconPapers)
Date: 2013
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:978-1-4614-6227-9_13

Ordering information: This item can be ordered from
http://www.springer.com/9781461462279

DOI: 10.1007/978-1-4614-6227-9_13

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 ().