I took this course in semester 1 - 2020 (online). Due to many people being caught cheating on the assignments the previous semester, the exam counted for 70% this time which made doing well more difficult.
The assignments (6 in total) are quite challenging and are not really worth the 5% but if you are keeping up with lectures and tutorials they shouldn't be too bad. The later topics involving Markov chains and reliability functions (a new topic added this semester), were in my opinion, some of the easier content in the course. It was also a great way to pick up marks in the exam.
In my exam, 15 marks/70 marks consisted just off reliability and 25/70 for both reliability and Markov chains. The process doesn't change for these questions so there isn't any unfamiliar elements in these. The rest depends on how well you understand the content.
In terms of difficulty, I would place it in between math2001 and math2400. In the applied maths major you have to pick between this course and a physics one. Personally, I am not as good at physics and I believe statistics will be more important in the industry hence why I chose to take this.
The lecturer was pretty good and understanding. Offered online consultations after every lecture (although I never utilised this), and the last two lectures just consisted of going over some past papers. A positive of this course is that solutions were provided for all the past exams on blackboard.
I would say the start of the course is moderately easy, then it pretty quickly becomes quite challenging around the mid point (introduction of ideas like inverse-transform Method, acceptance rejection method) which then goes into conditional probability. This involves many formulas and I feel like the structuring should have been given more attention.
I would really recommend you to split all the formulas into the four different cases and know when to use them. This takes some practise if you don't have anyone explaining it to you. The latter half is pretty easy which is nice. I think this is generally the case with all UQ courses though in terms of difficulty.
Also, make sure you know how to draw graphs of conditional probability and Markov chains because these appeared on the exam. You don't actually need to know any programming at all. Personally I skipped every time the lecturer discussed these ideas, but knowing the code for Matlab to draw these up helps.
Overall it's a pretty decent course. Definitely much harder than stat1201/stat1301 which are really quite basic in comparison. The intro to stat2003 will feel like a follow on from these courses but towards the middle is when it will probably put some people off.
The textbook is really just the course notes provided in blackboard and these can be really helpful!
Alright content but just shocking teaching style. You can't go into the blackboard because the lecturer doesn't record it properly. The teaching style was pretty good but just shocking teaching methods were taken place as silly 'punishments' like getting yelled at or recording student id numbers. Give this course to someone else who can manage a class!