NUS module reviews AY19/20 Y1S2

IMPORTANT NOTE: Do note that the following modules were taken during the COVID-19 pandemic and because of that, there were numerous changes to the teaching method and assessment components. As such, I will be writing how the module should be (if not for the pandemic) and how it has changed for a more accurate review.

  1. FAS1102: Public Writing and Communication

Tutor: Dr Noelle Catherine Wee


  • Tutorial participation: 20%
  • Individual/Group blog article: 35%
  • Group presentation: 35% –> Changed to online presentation via Zoom due to COVID-19 situation
  • Individual reflection letter: 10%

Webcast: N/A

Tutorials: Weekly two-hours

The whole course revolves just around two main things: writing a blog article and a group oral presentation. You have to form your own group (3 or 4), come up with a social issue and write/present on it. Things will be difficult at the start as you find an issue to write on but once it is settled, the other things should fall in place smoothly.

This is a compulsory public communication course for all FASS students so whether you like speaking or not, you have to do this module. As compared to FAS1101, FAS1102 definitely has a lighter workload and a more interesting scope. But, FAS1102 has weekly assignments (mostly graded as ‘tutorial participation’ only) to be submitted. While tiresome, I personally find this useful as it drills me to be focused on my topic and it does save some time when our group prepared for our blog and presentation. My tutor was rather strict in class but in terms of marking, I think she is not very strict. Go for regular consultations and follow the rubrics well and you should be fine.

Tip: Since you can form your own groups, do this class with your friends i.e. select the same class during ModReg exercise. It would be much more convenient and comfortable for yall since this module requires plenty of after-class group discussions.

2. GER1000: Quantitative Reasoning

Tutor: Chua Nam Chew

Tutorials: Odd/even, 5 tutorials in total

Workload (initial—>updated):

  • Class participation: 9% –> 10%
  • ExamSoft practice paper: 1% –> 0%
  • Weekly quizzes: 20% —> 25%
  • Project (Report + Presentation): 35% –> 45%
  • Finals MCQs: 35% —> 20%

GER1000 mainly focuses on teaching students how to read a research paper critically with respect to the numbers and figures used in one. Some of the topics covered are probability, hypothesis testing, types of sampling and differences between a cohort study and case-control study. While insightful, I personally do not find GER1000 relevant (yet). Good to know that there is no reading for this module.

There are quite a few calculations involved in this module and for stats major, or students who have/are taking stats-related module, GER1000 should be easy for you.

The project was surprisingly very manageable. It consists of two main parts: a 4-page summary of a research article and newspaper report, and a group presentation of it. The teaching team will release a list of questions to be covered for the report and presentation so what your team has to do is to simply answer the list of questions. Initially, the presentation was supposed to be conducted face-to-face but because of the COVID-19 situation, it was done via Zoom instead.

Weekly quizzes are manageable although it is still better if you join your cohort’s GER1000 Telegram group for further discussions of the questions. The finals for my batch only had 14 MCQs since we only had 1 hour (previously 2 hours). Because it’s all MCQs, it’s hella tricky.

FYI, the groupings are pre-allocated so there really is no point trying to do this class with your friends.

Tip: For econs students, do take EC2303 together with GER1000 since both have overlapping concepts, albeit only a little.

3. EC2101: Microeconomic Analysis I

Lecturer: Dr. Zhang Yang

Lectures: webcasted

Tutorials: weekly, one-hour


  • Tutorial attendance (5%)
  • Tutorial participation (5%)
  • Pair/group Homework 1 & 2 (15%)
  • Midterms (25%)
  • Finals (45%)
  • Pre-lecture quizzes (5%)

It is a core module for economics major and it basically covers four big concepts: consumer theory (preferences, budget line and optimal basket), producer theory (isoquant, isocost, cost-minimising choice of inputs), exchange economy and perfect competition in the SR and LR.

Dr. Zhang is really a funny lecturer who covers every single concepts in depth. I’m guessing it’s because she has taught this module for n number of times, she knows what misconceptions students will usually have. Ask any econs student and they will say that Dr. Zhang cracks great jokes and is a genuinely nice lecturer. I remember her telling us this joke as she was going through a lecture. So this particular slide had an empty spot on its left side and Dr. Zhang said that this was the invisible hand *face palms*.

While I find it content-heavy (maybe i feel this way because it’s my first lvl 2k mod), there’s really nothing much to memorise since the finals and midterms test you on your understanding. Good thing to know is that there is no reading, just textbook (quite light).

The homework sets are done in pairs or trios and are rather manageable and it is good to find someone reliable to do it with. The average is high at 14-14.5/15 lmao so this tells you something about the bellcurve for this module.

Both finals and midterms had MCQs and short-answer questions and as usual, MCQs are tricky and very time-consuming. For my batch, our finals were held over Examplify and needless to say, the navigation and everything was bad. We were only required to type in the key equations and workings for the finals. Not blaming anyone for this but I would say my performance was rather affected because I’m simply not used to doing an examination online.

Tip: Do EC2104 WITH EC2101 or EC2104 with EC1101E. Heard that doing EC2101 and EC2102 is ok but personally won’t do so because it’s rather content-heavy.

4. MA1505: Mathematics I

Lecturer/Tutor: Dr. Ng Wee Seng

Lectures: none. Watch pre-recorded videos released by lecturer (all-at-once) OTOT

Tutorials: weekly 2-hours


  • Class attendance (10%)
  • Class assignments (10%)
  • Lecture quiz (15%)
  • Finals (65%)

Took this module as preclusion to EC2104 simply because EC2104 was oversubscribed, so I’m guessing I’m one of the only few econs students who did not do EC2104 at all. Don’t even get me started on why I could not get EC2104. Just a friendly tip for all freshies: JUST declare your major first to secure the relevant 2k modules. You can change your major anytime (not after 5th semester if i’m not wrong, so JUST declare to have higher priority in ModReg)

Initially very very bitter over having to do this module and especially needing to do vectors again (After MA1301) but halfway through the semester, I’m glad I did this over EC2104.

To begin, MA1505 is a introductory mathematics course for ENGINEERING students. With that said, you can imagine the vast amount of vectors involved in this course and yes, that is true. The whole MA1505 centers around: partial differentiation, multiple integrals (and polar coordinates), vector functions, vector fields (calculating work done) and infinite series (Taylor, Maclaurin, Fourier series). But fortunately, this module does not require any background in engineering or physics; it only requires us to solve the questions. Simply put, it is a math exam with lots of integration, trigonometry, differentiation and vectors.

And why did I say I prefer this over EC2104?

  • NO lectures at all (except for one briefing lecture on week 1). Everything was taught via pre-recorded videos by the prof and he releases all videos at once. This means that you can really do things at your own pace although he has a recommended weekly study plan. And this brings me to my next point:
  • The whole module was very well-organised.
    • The teaching materials were very comprehensive (we had summary notes for every chapter?!). Lots of practice papers to work on.
    • The tutorial questions also had labels to tell us which example in the lecture notes we should refer to while solving.
    • Each week we were told what chapters to cover and what tutorials to do. Not gonna lie but I feel this is important for students but sadly, some other modules are rather vague on the timeline.
  • Gotta say the lecturer who was my tutor too was very patient in teaching and clearing up common misconceptions.
  • Weekly-in class assignments were effective in making us understand key concepts.
    • so basically in each tutorial, the tutor will go through the key concepts for each chapter. then he will go through every question from the tutorials.
    • afterwards, the tutor will give you this worksheet (with two questions) where you are expected to finish and submit by end of class.
    • you can consult the prof, discuss with your friends if you have any doubts.
    • and my tutor gives us the final answers for each question so in a way, you know whether you are doing it right or wrong.
  • We are allowed to bring in CHEAT SHEETS for exams LOL this will never exist for econs modules

The finals were pretty manageable and the questions required no engineering knowledge at all. It was held over LumiNUS and the exam was divided into two segments. For each segment, we had to write our workings on blank A4 papers, scan and upload to LumiNUS. Gotta say this was certainly the most logical and easiest way of conducting the examinations online. And it sure is fair too because sometimes our final answers may be wrong but with this, we can still earn some working marks.

Surprisingly, I found myself enjoying this module although the content will 99% not gonna be relevant to me in the future lmao.

5. DAO1704X: Decision Analytics using Spreadsheets

Lecturer: Tung Yi-Liang

Lectures: webcasted (each lecture valid for only 2 weeks)

Tutorials: weekly one-hour


  • Tutorial participation (15%)
  • Individual assignment x 2 (15%)
  • Group project (15%)
  • Weekly LumiNUS quizzes (15%)
  • Finals (40%)

This was by far the weirdest module I’ve ever taken in NUS. DAO1704/DAO1704X is something like an introductory module for the business analytics specialisation offered under the NUS Business School. But as its name suggests, this module is all about solving problems via MS Excel. For starters, it requires basic knowledge of Microsoft Excel because you will be relying heavily on it for your assignments, quizzes etc.

Do note that the workload is for the X-coded DAO1704X. For business students, this module is simply DAO1704. The content is the same but the assignments may slightly differ to cater to the non-business students.

The four main themes in this module are: probability, decision trees, linear programming and sensitivity analysis, and discrete optimisation. The odd part is the four main topics aren’t very linked to one another so the whole course itself just seems very out of place at times.

At the beginning, the theme of probability takes up at least 5 lectures and it covers the basic probability concepts like normal distribution, exponential distribution and joint probability distribution. While it might seem tough, it is pretty manageable because you do not have to use or apply any mathematical formula for it; you just need to write in the Excel formula e.g. =BINOM.DIST(x,n,p,TRUE/FALSE) for your final examinations. This is one reason why I found the course weird. But anyways, that’s the part on probability.

The next big topic is on decision trees and it oddly takes up just one whole chapter. This is closely linked to probability and it is one of those topic where if your first few steps are wrong, the subsequent workings will definitely be wrong and I’m guessing this was what happened to me for finals :/

Lastly, linear programming is basically about optimising a problem given a constraint. Don’t be afraid of the term though because there is literally no computer programming here. We are just using Excel’s built-in Solver to solve problems. For econs students, this is literally the case of utility maximisation and cost-minimising. There will be lots of graph drawings for this theme so you’ve gotta be comfortable with graphs, calculating gradients etc. Sensitivity analysis falls under this because it is about examining the change to an objective value and optimal solution when one of the objective coefficient or constraint coefficient changes. It is pretty intuitive once you actually understand the whole graph-drawing part. Discrete optimisation is similar to LP except that there are some decision variables that are binary (yes or no/ 1 or 0) and/or integers-only.

How was the assignments like for this module? Well for the first individual assignment, I barely passed it because it mainly covers probability concepts and I was rather confused with the different types of probability distributions at the beginning. The second one was slightly better as it did not had any probability questions.

The final for this module was very interesting. So, there are four main questions with each question dedicated to a specific theme – probability, decision tree, linear programming and sensitivity analysis, and discrete optimisation. You can just leave your answers in terms of Excel formula for this module. And as for the remaining topics involving Excel’s Solver, there will be a screenshot of the Excel cells, Solver’s Answer Report and Sensitivity Report given and you have to analyse and write your answers. I still cannot get over how weird this format is but ok.

Have very mixed feelings about this module as I was often confused by the class content. Morover, the whole semester was very disruptive to begin. We were supposed to have F2F one-hour tutorials every week but one of our TA was in Hubei and hence, she could not fly back to Singapore. In the end, our prof took over the physical tutorials for two weeks followed by another two weeks by another TA. No Zoom lessons were conducted after the whole COVID-19 situation worsened and we simply watched videos of our prof and TA explain tutorial questions and quizzes. So, our tutorial participation is essentially a given so long as you finished watching the required videos per week.

Tip: for those planning to do this for UE, do be aware that there might be seniors from other faculties who have done stats/math modules before doing this. This can kinda affect the bellcurve.

Overall, would say that this semester was significantly better than my first semester in terms of workload. There was almost no readings or papers to read and write because everything was just math-based (Except FAS1102).

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