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Rank Correlation Methods

Rank Correlation Methods
Author: Maurice George Kendall
Publisher:
Total Pages: 220
Release: 1962
Genre: Correlation (Statistics).
ISBN:

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Public Program Analysis

Public Program Analysis
Author: Ronald Forthofer
Publisher: Springer Science & Business Media
Total Pages: 305
Release: 2012-12-06
Genre: Science
ISBN: 1468466836

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The past two decades have witnessed a dramatic increase in the demand for analyses of health and public affairs program data. Governments at the federal and state levels have stimulated, if not mandated, much of this increased de mand and spawned numerous not-for-profit and quasi-public organizations research groups, lobbying organizations, consulting firms-who actively use analytic techniques. Program analysis is a broad term that encompasses activities such as pro gram planning and prediction, program assessment, and program evaluation. Though purposes differ and techniques vary, the common denominator for all applications is the attempt to use quantitative techniques to provide compre hensive and objective analyses. Program analysis in public health and public affairs shares another common feature: In many cases the data collected for these applications are categorical in nature-that is, discrete information rep resented by categories. Whether a defendant in a criminal trial is convicted (yes, no), the number of times a person visits a community health center in a month (0,1,2,3, ... ), how a person feels about a proposed program (agree, disagree, not sure, no opinion)-these are examples of categorical data. This book describes a multivariate categorical data analysis technique the weighted-least-squares (WLS) approach developed by Grizzle, Starmer, and Koch (GSK)-applied to program analysis in health and public affairs. It is written for in-service professionals who desire an introduction to applied cate gorical data analysis and for preservice students who are studying quantitative methods.


Rank correlation methods

Rank correlation methods
Author: Maurice G. Kendall
Publisher:
Total Pages: 202
Release: 1975
Genre:
ISBN:

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Rank Correlation Methods

Rank Correlation Methods
Author: Maurice George Kendall
Publisher: Hodder Education
Total Pages: 280
Release: 1990
Genre: Correlation (Statistics).
ISBN:

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Rank Correlation Methods; 3rd Edition

Rank Correlation Methods; 3rd Edition
Author: Maurice G (Maurice George) Kendall
Publisher: Hassell Street Press
Total Pages: 218
Release: 2021-09-09
Genre:
ISBN: 9781014493095

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This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.


Rank Correlation Methods

Rank Correlation Methods
Author: Maurice G. Kendall
Publisher:
Total Pages: 0
Release: 1962
Genre:
ISBN:

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Rank Correlation Methods

Rank Correlation Methods
Author: Sir Maurice Kendall
Publisher:
Total Pages: 199
Release: 1962
Genre:
ISBN:

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Statistical Methods for Ranking Data

Statistical Methods for Ranking Data
Author: Mayer Alvo
Publisher: Springer
Total Pages: 276
Release: 2014-09-02
Genre: Mathematics
ISBN: 1493914715

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This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.