Working with Variable Types and Labels in Jamovi

Setting up your data correctly is the most critical first step in statistical analysis, and misclassifying variables can lead to incorrect statistical tests and flawed results. This comprehensive text-based guide teaches you how to organize, categorize, and document datasets efficiently using Jamovi. You will gain a solid foundation in statistical measurement levels, discover how Jamovi handles different data formats, and develop best practices for clean data management that support reproducible research. What you'll learn: - Understand the core differences between nominal, ordinal, and continuous measurement levels - Configure variable types, measure types, and data formats inside Jamovi - Create meaningful variable labels and assign descriptive value labels to categorical data - Manage missing data values and recode variables systematically - Apply tidy data principles to prepare datasets for exploratory analysis - Explore modern reproducible workflows using Jamovi's integrated R syntax mode The course begins with foundational statistical definitions and data terminology before progressing step-by-step through practical variable management techniques and structured data preparation scenarios. This course is designed for absolute beginners, students, and researchers who want to master data setup in Jamovi without requiring any prior statistical or programming experience. Start reading today to build well-structured datasets and ensure your data analyses are accurate and reproducible.