Data Filtering and Case Selection in Jamovi

Working with real-world datasets often requires analyzing specific groups or isolating subsets of participants. This text-based guide teaches you how to confidently filter cases and manage data structures using Jamovi. You will learn to write filter expressions, exclude outliers or invalid responses, and ensure clean datasets for your statistical evaluations. What you'll learn: Understand foundational data types, variables, and logical filtering concepts in Jamovi; Create simple and multi-condition filters using logical operators; Handle missing values and outlier exclusions systematically; Apply dynamic filtering rules to maintain reproducible analysis workflows; Combine filtered subsets with descriptive statistics and summary tables. The course begins with essential statistical data concepts and Jamovi terminology before walking through practical filtering scenarios step by step through written explanations and examples. This guide is designed for beginners, researchers, and students with no prior programming background required. Start reading to build reliable data filtering skills in Jamovi today.