There is debate over the functional basis of student evaluations of academics, and fresh potential for looking at the data in new ways. Student evaluation data was collated over a three year period (Semester 2 2015 to Semester 1 2018). We used a General Linear Model to estimate the variation in course scores explained by a number of coordinator and course attributes. Three significant factors collectively explain 49% of the School's variation in course scores--individual coordinator, student evaluation response rate, and mode of delivery. Next, we used hierarchical clustering to explore the inter-relationships among the eight course and teaching evaluation questions. Learning appears to be related to stimulation, whereas overall satisfaction appears to be related to quality of learning materials and course structure (i.e. aspects of course organisation). Student evaluation response rate is positively correlated to all eight course questions, but most positively to a question relating to receiving adequate feedback. This perhaps implies some reciprocity in the flow of information between student and coordinator. The overall teaching rating awarded to academics clusters most with approachability and encouragement of student input--aspects of temperament and style--and not with explanatory skill or organisational ability.