Factor Analysis in Jamovi for Beginners

Understanding complex multi-variable datasets can be overwhelming without the right statistical tools. This text-based course guides you through conducting, interpreting, and reporting factor analyses using the user-friendly statistical platform Jamovi. You will gain the practical knowledge required to reduce data dimensionality, validate survey instruments, and identify hidden latent constructs with confidence. What you'll learn: - Understand foundational factor analysis principles, core terminology, and variance concepts - Prepare and evaluate datasets using modern assumption checks, sampling adequacy tests, and correlation matrices - Perform Exploratory Factor Analysis (EFA) to discover latent dimensions within multi-item measures - Apply appropriate extraction methods and rotation strategies to improve factor interpretability - Examine Confirmatory Factor Analysis (CFA) basics to test and validate theoretical models - Interpret output metrics including factor loadings, uniqueness, eigenvalues, and scree plots - Apply modern reporting standards and reproducible documentation practices for academic and business research The course begins with fundamental definitions and conceptual foundations before walking through structured analytical steps and practical data interpretation scenarios. This course is designed for students, researchers, and data professionals who want a clear, step-by-step introduction to factor analysis in Jamovi without complex mathematics. Start reading to build your statistical analysis skills and uncover valuable insights in your data.