Lower Bounds for Percentiles of Pivots from a Sample Mean Standardized by S, the GMD, the MAD, or the Range in a Normal Distribution and Miscellany with Data Analysis

Nitis Mukhopadhyay ()
Additional contact information
Nitis Mukhopadhyay: University of Connecticut

A chapter in Strategic Management, Decision Theory, and Decision Science, 2021, pp 87-108 from Springer

Abstract: Abstract This paper begins with a one-sample normal problem and considers a number of pivots, generically denoted by H, obtained from the sample mean ( $$\overline{X}$$ X ¯ ) when it is successively standardized by the following statistics: (i) sample standard deviation (S), (ii) Gini’s mean difference (GMD), (iii) mean absolute deviation (MAD), and (iv) range (R). In each case, we have developed useful and explicit lower bounds for the upper $$100\alpha \%$$ 100 α % point for the probability distribution of H, $$0

Keywords: Behrens-Fisher situation; Concave function; Convex function; Cornish-Fisher expansion; Data analysis; Gini’s mean difference (GMD); Jensen’s inequality; Mean absolute deviation (MAD); 60E15; 62E17; 62L12; 62H10 (search for similar items in EconPapers)
Date: 2021
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:978-981-16-1368-5_7

Ordering information: This item can be ordered from
http://www.springer.com/9789811613685

DOI: 10.1007/978-981-16-1368-5_7

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 ().