Summary
Contents
Subject index
Data Analysis in Business Research: A Step By Step Nonparametric Approach discusses tools pertaining to one-sample tests, two independent sample tests, k-independent sample tests, two-related sample tests, k-related sample tests, measures of correlations and associations, tests of interactions and multiple comparisons and, multivariate interdependence test using correspondence analysis. The book features:Non-technical coverageLucid presentation for easy comprehensionIllustrated step-by-step approachCompendium of major non-parametric tests in one textComprehensive quiz bankWould be widely applicable in all disciplinesA friendly guide in doing the dissertation data analysisThis book is designed as a supplementary text for students of business and management. It will also be useful for marketing professionals and market research organizations.
Measures of Correlation and Association
Measures of Correlation and Association
In this chapter various measures of correlation and association are presented. The Spearman's Rank Correlation Coefficient is used for measuring the relationship between 2 ordinal variables. While phi-correlation coefficient is used for testing the degree of association between 2 dichotomous variables, the Contingency Coefficient is useful to find out the degree of association between 2 nominal variables, each with ‘n’ number of categories. The Cramer's V coefficient is an extension of Contingency Coefficient and is used to analyse the relationship between 2 nominal variables with ‘n’ number of categories, with an upper correlation coefficient of 1. The Goodman–Kruskal Lambda measures the association between 2 variables that are measured on nominal scale—each variable with 2 or more ...
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