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Introduction to modern nonparametric statistics / James J. Higgins.

By: Material type: TextTextPublication details: [S.l.] : Duxbury Press, 2003.Edition: 1st edDescription: 384 p. ; 24 cmISBN:
  • 0534387756 (hardcover)
  • 9780534387754 (hardcover)
Online resources: Summary: Guided by problems that frequently arise in actual practice, James Higgins' book presents a wide array of nonparametric methods of data analysis that researchers will find useful. It discusses a variety of nonparametric methods and, wherever possible, stresses the connection between methods. For instance, rank tests are introduced as special cases of permutation tests applied to ranks. The author provides coverage of topics not often found in nonparametric textbooks, including procedures for multivariate data, multiple regression, multi-factor analysis of variance, survival data, and curve smoothing. This truly modern approach teaches non-majors how to analyze and interpret data with nonparametric procedures using today's computing technology.
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Item type Current library Collection Call number Status Barcode
Book Book Air University Central Library Islamabad NFIC 519.5 HIG (Browse shelf(Opens below)) Available P3575

Guided by problems that frequently arise in actual practice, James Higgins' book presents a wide array of nonparametric methods of data analysis that researchers will find useful. It discusses a variety of nonparametric methods and, wherever possible, stresses the connection between methods. For instance, rank tests are introduced as special cases of permutation tests applied to ranks. The author provides coverage of topics not often found in nonparametric textbooks, including procedures for multivariate data, multiple regression, multi-factor analysis of variance, survival data, and curve smoothing. This truly modern approach teaches non-majors how to analyze and interpret data with nonparametric procedures using today's computing technology.

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