Chi-Squared Tests of Association in jamovi

Analyzing relationships between categorical variables is a fundamental skill in modern research and data analysis. This text-based course provides a structured introduction to conducting, interpreting, and reporting Chi-Squared Tests of Association using jamovi, an intuitive open-source statistical software. You will build a solid grounding in statistical theory, understand how cross-tabulation works, and gain the practical skills needed to test hypotheses on real-world categorical data. What you'll learn: - Understand foundational concepts of categorical data, contingency tables, and null hypothesis testing - Prepare and format tabular data for statistical evaluation in jamovi - Perform Chi-squared tests of association and evaluate expected frequency assumptions - Apply appropriate corrections and alternative tests such as Fisher's exact test when assumptions are unmet - Calculate and interpret effect size metrics, including Cramér's V and the phi coefficient - Report and document analytical findings clearly following standard academic formats The course begins with essential statistical terminology and basic cross-tabulation principles before walking through complete analytical workflows and practical interpretation scenarios. This course is tailored for beginners, students, and professionals seeking a straightforward, practical introduction to categorical hypothesis testing without complex mathematics or prior software experience. Read through the lessons and start analyzing your categorical data effectively.