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25 Remote Warehouse Sociology- Reference and Methodology

Quantitative Applications in the Social Sciences #08: Analysis of Ordinal Data

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Quantitative Applications in the Social Sciences #08: Analysis of Ordinal Data Cover

 

Synopses & Reviews

Synopsis:

Ordinal data can be rank ordered but not assumed to have equal distances between categories. Using support by judges for civil rights measures and bussing as the primary example, this paper indicates how such data can best be analyzed.

Synopsis:

This monograph indicates how such data can best be analyzed. It is important because it applies a conceptual scheme recently developed by the authors-prediction analysis-to ordinal data.

Product Details

ISBN:
9780803907959
Author:
Hildebrand, David K.
Publisher:
Sage Publications, Inc
Author:
Rosenthal, Howard
Author:
Laing, James D.
Location:
Beverly Hills, Calif. :
Subject:
Statistical methods
Subject:
Research
Subject:
Social sciences
Subject:
Numbers, Ordinal
Subject:
Social sciences -- Statistical methods.
Subject:
Sociology-Reference and Methodology
Edition Description:
Bibliography: p. 78-79.
Series:
Quantitative Applications in the Social Sciences
Series Volume:
ser. no. 07-008
Publication Date:
19770531
Binding:
TRADE PAPER
Language:
English
Illustrations:
Yes
Pages:
80
Dimensions:
850x550

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Related Subjects

Health and Self-Help » Health and Medicine » Medical Specialties
History and Social Science » Sociology » Reference and Methodology
Religion » Comparative Religion » General
Science and Mathematics » Mathematics » Applied
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

Quantitative Applications in the Social Sciences #08: Analysis of Ordinal Data New Trade Paper
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$22.75 In Stock
Product details 80 pages Sage Publications - English 9780803907959 Reviews:
"Synopsis" by , Ordinal data can be rank ordered but not assumed to have equal distances between categories. Using support by judges for civil rights measures and bussing as the primary example, this paper indicates how such data can best be analyzed.
"Synopsis" by , This monograph indicates how such data can best be analyzed. It is important because it applies a conceptual scheme recently developed by the authors-prediction analysis-to ordinal data.
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