The document discusses using quantitative usability testing data to understand why users behave in certain ways. It emphasizes that quantitative findings are more powerful when accompanied by qualitative explanations. Theories and hypotheses can provide these "why" explanations by predicting how users will interact with a design and what barriers they may face. Different types of hypotheses are outlined, including ones based on the design itself, other data sources, stakeholder views, and methods used. Remote unmoderated usability testing is presented as a way to gather data to evaluate these hypotheses and better understand users' motivations and challenges.