It is a statistical tool used to examine the association between two categorical variables in small sample sizes, especially in 2×2 tables. It provides an exact p-value and is preferred over the Chi-Square Test when expected frequencies are low (< 5). It is widely used in fields like medical and clinical research for accurate analysis with limited data.
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Analysis of Variance Before-After Test Chi-Square Test Chi-Square Test of Independence Conceptual Framework Confounding Variable Contingency Table Control Variables Correlation Analysis Data Analysis Dependent Sample 't' Test Dependent Variable Descriptive Statistical Analysis Distribution-Free Test Formulation of Research Problem Framing Objectives of Research How to Identification of Research Problem Independent Variable Inferential Statistical Analysis Linear Regression Matched Paired Sample 't' test Mediating Variable Moderating Variable Multiple Regression Analysis Non-Parametric Test One-Way ANOVA Paired Sample 't' Test Pearson Problem Statement Qualitative Analysis Quantitative Analysis Questionnaire Preparation Regression Analysis Relationship Repeated Measures ANOVA Research Design Research Guidance Research Objectives Research Questions Selection of Variables Simple Regression Spearman Two-Way ANOVA Variable Types