Some Further Issues in One-Factor Designs and ANOVA

Paul D. Berger, Robert E. Maurer and Giovana B. Celli
Additional contact information
Paul D. Berger: Bentley University
Robert E. Maurer: Boston University, Questrom School of Business
Giovana B. Celli: Cornell University

Chapter Chapter 3 in Experimental Design, 2018, pp 69-105 from Springer

Abstract: Abstract We need to consider several important collateral issues that complement our discussion in Chap. 2 . We first examine the standard assumptions typically made about the probability distribution of the ε’s in our statistical model. Next, we discuss a nonparametric test that is appropriate if the assumption of normality, one of the standard assumptions, is seriously violated. We then review hypothesis testing, a technique that was briefly discussed in the previous chapter and is an essential part of the ANOVA and that we heavily rely on throughout the text. This leads us to a discussion of the notion of statistical power and its determination in an ANOVA. Finally, we find a confidence interval for the true mean of a column and for the difference between two true column means.

Date: 2018
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:978-3-319-64583-4_3

Ordering information: This item can be ordered from
http://www.springer.com/9783319645834

DOI: 10.1007/978-3-319-64583-4_3

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 ().