Paired vs Independent Samples

Statistics · Axiom Academy

INTRO Independent vs Paired Samples Discover how the structure of your data changes the way you analyze it. Imagine you're testing whether a new study technique improves test scores. How you collect your data matters! Drag the people below into the appropriate category. Different people in each group When you measure the same person twice, you can track individual changes. Adjust the sliders to see how each person's score changed after using the new study technique. Independent Samples: Different People Now imagine a different experiment: we randomly assign students to use either the new technique or the old technique. Click on a group to see their scores. Different research questions require different designs. Click each scenario to see whether it uses independent or paired samples. Structure: Two separate groups with different subjects Question: "Is Group A different from Group B?" Example: Treatment group vs control group Analysis: Compare group means using a two-sample test Structure: Same subjects measured twice (or matched pairs) Question: "Did subjects change from condition 1 to condition 2?" Example: Before/after measurements, twin studies Analysis: Compare differences within pairs using a paired test The statistical test you use depends on your data structure. A paired t -test analyzes differences within pairs, while an independent t -test compares between groups. Using the wrong test can lead to incorrect conclusions!

This is the written version of the interactive lesson above. See the full Statistics course.