Course content is good - you will have better understanding on scientific literature and interpret the results right.
Lectures - not bad, but Problem based learning is a essential of this course. PBLs will help you understand everything that you don't understand about the content, by asking questions addressing what's exactly required to be known.
Pracs using R needs a bit of preparation, although they do not ask you to do so. It was sometimes overwhelming because there were some of 'extra' works to be done on the dataset and R code which prac manuals do not cover + as an external student (covid), it was extremely hard to explain problems on my R studio and my small laptop constantly made errors on presenting graphs due to small screen size. Pls at least prepare a dual monitor to watch the live prac instruction and follow the process on your own screen at the same time. Otherwise you have to switch screen too many times.
I really liked this course! Only having one lecture a week, but then reinforcing the concepts from that lecture by going over it in the pracs and PBL was really refreshing and really helped me to properly learn, instead of feeling overwhelmed with loads of content I didn't understand. The lecturers are also really friendly and willing to help. I really recommend this course if you have an interest in statistics but don't want to get too bogged down with numbers - the course is more about statistics concepts then pure math.
This is, by far, the worst course I've ever taken.
The stats aren't too difficult but you better understand them after one lecture and one PBL because there is absolutely no learning material. No textbook, no worked examples on blackboard, no past exam or sample exam answers. Nothing. You get the one example you do in your PBL and the only two sessions are on the same day so if you are unable to attend you won't have anything. No PBL or prac answers are uploaded. Take photos of your quizzes when you get them back because that and the PBL is all you'll have to study for the exam. Also, many of the questions on the final are almost exactly like the quiz questions.
Lecturers are nice enough but if you ask them for worked examples or questions to study they just tell you to look at previous exams, even at the start of the semester.
Topics are disjointed, you don't learn a topic at one time but rather split up throughout the semester.
The prac manual is digital and you need to do a special installation to use it outside of the labs.
This course was a nightmare. Not that the concepts were overly complex or difficult, but the presentation of it all was atrocious. Numbers are thrown at you without any explanation of where they came from or what they mean. It all felt far too disconnected from any mathematics, which would have helped give context. The lecturers were dull and mostly bad at explaining concepts, although that might have been due to the aforementioned issues. Furthermore additional lectures on an already introduced topic were scheduled weeks after orignal leanring about it. The prac and PBL session may be the only saving grace. The tutors I have were excellent and always helped clarify the mess of information we had been fed in the lecturers.
The course was very well structured, it was very helpful having most of the contact hours allocated to practicals instead of lectures as it helped solidify the content. Learning how to use R was perhaps the most useful part of the course, I hope the School will come out with more statistics courses as it would be vital for honours year. The course was enjoyable and I learnt a lot more than in STAT1201 as the content was more related to my major and interests. The lecturers and tutors were all very helpful, and you could tell they wanted us learn and become proficient at statistics and using R by simplifying the concepts.
Semester 1 - 2014
Environmental Science (Ecology)
Is lecture attendance necessary?
Is the textbook necessary?
No - I never used it
Very well structured course
Lecturers and tutors were helpful
Practical skills gained (R)
Could have introduced more complex statistical concepts