Inferences About Robust Measures of Location

Rand R. Wilcox ()
Additional contact information
Rand R. Wilcox: University of Southern California College of Letters, Arts & Sciences, Department of Psychology

Chapter Chapter 9 in Fundamentals of Modern Statistical Methods, 2010, pp 147-167 from Springer

Abstract: Abstract For most purposes, simply estimating a measure of location is not sufficient. There is the issue of assessing the precision of an estimate, and of course there is the related problem of testing hypotheses. How do we test hypotheses or compute confidence intervals with a trimmed mean or an M-estimator of location? To what extent do such methods address the problems with Student’s T listed in Chapter 5? These issues are discussed in this chapter.

Keywords: Error Probability; Bootstrap Sample; Probability Coverage; Normal Curve; Robust Measure (search for similar items in EconPapers)
Date: 2010
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:978-1-4419-5525-8_9

Ordering information: This item can be ordered from
http://www.springer.com/9781441955258

DOI: 10.1007/978-1-4419-5525-8_9

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 ().