  We analyze learning data of an e-assessment platform for an introductory
mathematical statistics course, more specifically the time of the day when
students learn. We propose statistical models to predict students' success and
to describe their behavior with a special focus on the following aspects.
First, we find that learning during daytime and not at nighttime is a relevant
variable for predicting success in final exams. Second, we observe that good
and very good students tend to learn in the afternoon, while some students who
failed our course were more likely to study at night but not successfully so.
Third, we discuss the average time spent on exercises. Regarding this, students
who participated in an exam spent more time doing exercises than students who
dropped the course before.
