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Title: Tests of independence : a state of art
Authors: Frangieh, Charbel
Advisors: Sabat, Mira 
Keywords: Test for independence, nominal variables, ordinal variables, numerical variables, contingency table, non-fixed marginal, multiple response data, correlation
Subjects: Statistics
Language arts
Mathematical statistics
Dissertations, Academic
University of Balamand--Dissertations
Issue Date: 2021
The purpose of this project is to investigate the methods used to test the independence between random variables (nominal, ordinal and numerical). For every test, the hypothesis used, the p-value, the assumptions and conditions are stated. The nominal and ordinal variables are illustrated in a contingency table. The independency between categorical variables is considered in the cases of fixed and non-fixed marginals and in the case of multiple response data. The correlation coefficient is used for numerical data in order to test the level of association between two samples. All tests are illustrated by examples. The tests are then applied on a survey done at the University of Balamand (Sabat et al, 2020). The tests used to test the dependency between nominal variables are Pearson’s Chi-Square test, Likelihood Ratio test, Fisher Exact test, McNemar Test and their continuity corrections. As for the ordinal data, Cochran-Armitage and its continuity correction is considered. Moreover, multiple response data is approached by First Order Rao-Scott Chi-Square test. Lastly, Pearson’s correlation and Spearman’s correlation with ranks are studied for numerical data.
Includes bibliographical references (p. 59-61)
Rights: This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder
Type: Project
Appears in Collections:UOB Theses and Projects

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