It refers to the number of values that can vary freely in a statistical calculation. In a Chi-Square Test, it helps determine the correct distribution for finding the p-value. It is calculated as: (number of rows – 1) × (number of columns – 1) for a contingency table. The concept helps define the number of independent comparisons possible in a statistical test.
« Back to Glossary IndexAuthor
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