Chapter 5 Module 4: Drawing Conclusions - Interpreting Problems and Results
Welcome to one of the most critical skills in data science—learning how to draw valid conclusions from data and understanding what those conclusions can and cannot tell us. This module focuses on the thinking skills that separate good data science from misleading claims.
Interpreting Problems and Results isn’t about complex statistical tests or advanced mathematics. It’s about developing the intellectual honesty and critical thinking skills to say, “Based on this data, here’s what we can reasonably conclude, here’s what we’re not sure about, and here’s what we still need to investigate.”
Watch this video showing how students learn to make evidence-based claims.
By the end of this module, you’ll have practical strategies to help your students make reasonable claims based on evidence, express appropriate uncertainty, avoid common interpretation mistakes, and understand when their conclusions can be applied beyond their original data.
