Learning Materials: The lectures mainly followed the handouts. The lecture handouts are comprehensive and detailed! There were tutorial sheets used for the pracs and solutions were uploaded toward the end of semester to help with revision. Unfortunately, lectures were not recorded but it is ok to review the notes if you missed a lecture.
Learning Activities: Most of the content is covered during the lectures and applied in the practicals. Some pracs were a bit rushed though. There aren't many tutorial sheets to practice theoretical questions since it is mainly proofs or theorems.
Blackboard Management: Lecture handouts and tutorials sheets were regularly uploaded onto blackboard. The assignments were also uploaded onto blackboard and announcements made when appropriate.
Course Content: Course content is very theoretical (and dry at times) but the pracs and assignments help with digesting the content. Some of the linear algebra can be intimidating at first! Helps with understanding experimental design and the inner workings of ANOVA, regression etc.
Course Structure: The course followed a logical order but finite population sampling at the end felt a bit rushed.
Contact Availability: Geoff was great and very approachable. Lots of contact time and emails sent out about important dates and notices. Tutors were helpful during the pracs for assignment help.
Course Difficulty: The most difficult part of the course is understanding the content. You may feel lost for the first few weeks but will make more sense once you do the assignments. There’s a lot of proofs and theorems but the lecture handouts are comprehensive. It may take time to sit down and go over the lecture notes though.