{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/ad76fd1e9c6d4d649a0923849e98687c\" frameborder=\"0\" width=\"1908\" height=\"1431\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1431,"width":1908,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1431,"thumbnail_width":1908,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/ad76fd1e9c6d4d649a0923849e98687c-20185b4583a04786.gif","duration":356.768,"title":"Interpreting Benchmark Reports in Reputation Datasets","description":"In this video, I explain how to interpret the benchmark reports in our reputation data sets. We can perform three types of benchmarking comparisons: against other universities, entire peer lists, or regions. I walk you through the first benchmark report, highlighting how to read the charts, including the significance of the yellow line and the interquartile range. Additionally, I emphasize the importance of the vertical axis when zooming in on specific data. If you have any questions, please feel free to reach out to our AI chatbot or explore our library of articles and video tutorials."}