The Mathematical statistics division at Lund University teaches 8 core and 13 elective statistics courses within 14 different engineering programmes leading to Master of Science in Engineering. This paper uses cases to analyse the combination of ingredients that seems to make the difference between success and otherwise in design of curriculum for engineering programmes. The key aspects underpinning the efforts seem to be collaborative curriculum development, and a joint view from both engineering and statistics of the role of mathematics and statistics in technology and engineering. This respect and high regard for mathematical statistics from the engineering side, often arising from research or other collaboration, changes them from clients to partners. This paper is an attempt to systematize what we see as the important success factors in an engineering statistics education.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education