AY2015-2016 Semester 1 Module Review

I am very grateful that I got over 30 MCs with results that isn't too far from my expectations. Actually, 30 MCs wasn't as bad as I thought especially after I submitted my thesis. Since I only have 15 MCs to do a review for, I shall try to be even more detailed this time round.

EC4103 Singapore Economy: Practice and Policy

I have much grievances over this module. It is nothing but a burden. Ask me to name anything I learnt from it and I won't even be able to think of a single thing. Probably how to follow instructions and carry out the commands in Stata? Right, so this module was introduced this semester as many employers have given feedback that NUS EC graduates can only regurgitate theory but aren't so well-versed when it comes to knowledge of the Singapore economy. Although this may be true to a certain extent, this module is definitely not gonna help much in that aspect. I honestly think the way the module is taught needs to undergo some serious revisions.

How does this module work? There are 5 lecturers and each of them assesses 20% of the course. Depending on the lecturer, there could be 2 or 3 reports to hand up over that 2 or 3 weeks. If not, presentations had to be made. Occasionally, presentation slides had to be submitted as well. This cycle continued and I think there were about 8 written assignments in total over the entire semester. Every assignment had to be presented and so on top of the additional presentations, there were a total of about 10 presentations. Initially, the module started out slow and steady with the report having a page limit of two sides. Then it became worse with each lecturer, with the last lecturer allowing a page limit of 5 to 7 pages. There were 5 themes in total. Aamir Hashmi took the first one and it was, in summary, on the macroeconomics of Singapore i.e. the characteristics of its economy etc. Danny Quah was next and took the part on growth if I didn't remember wrongly. Then came Ivan Png who taught Singapore productivity. Up next was Jessica Pan who taught income inequality. Last was Chia Ngee Choon who took the aspect of Singapore budget policies. Or was it taxation? I can't really remember but it was something along those lines. 

The bottomline is this: lectures are pretty much useless if you're talking about scoring for this module. Actually, even for the purposes of learning, the lectures still remain useless. The thing is the assignments had absolutely nothing to do with what was taught in lectures. The only thing that you need to know is how to surf the net and look for relevant information. So it wasn't surprising that the turnout for the lectures was just getting more and more pathetic by the week. I did not attend lectures at all but still managed to get away with a decent grade. The assignments by the first two lecturers started off as generic essay-based questions so you could say that it's pretty much a test of general knowledge. Then they became Stata-based with the next two lecturers. And the last lecturer's was simply basic calculations using Excel. Needless to say, the assignments of these three lecturers required students to obtain the correct results as well as to analyze the results. For Ivan Png's, all we had to do was simply to follow the step-by-step instructions in the assignment using Stata and then analyze the regression results. Jessica Pan's part was a lot harder in comparison as hers was not so straightforward so a lot of people had difficulties. But the tutor (Kelvin Seah) was always ready to help and you can actually check with him if the graphs and results you got were correct. And this was important as correctness is a major determinant of your score for Jessica Pan's segment as is the case for Ivan Png's as well as Chia Ngee Choon's parts though the other two lecturers weren't so flexible with the validation of answers.

This module consumed a lot of my time every week but really, I got nothing out of it. It came to a point that the workload was so heavy that I found the completion of assignments and preparation for presentations becoming increasingly burdensome. Among all the 5 themes, I picked up pretty much zero stuff. Before I took this module, I know so much about Singapore. After completing this module, I still know as much about Singapore. That's how helpful the module had been. By the way, this module is fully groupwork. After being assigned a tutorial group, you will be assigned to your groups. You don't get to choose your group members. So if you and your friends are in the same tutorial group but do not have different starting letters for your names, then you don't have to think of being in the same project group. Cos how they assigned the groups was a no-brainer. They simply went by alphabetical order and grouped say, ABCD together in one group, EFCG in another and so on. Anyway, this is pretty crucial. Your grade is highly determined by peer review as much as I thought it didn't play a big role. After submission of each report, your group members are supposed to rate you and not to worry, it's confidential. I gave high ratings for my group members but it ended up that two (out of three) of them got a grade lower than me.

Result: A-

I was surprised by this grade as it exceeded my prediction of a B+ or worse. I am really thankful to my group members for giving me good reviews (as they said). Of course, that comes with a price as I was doing a lot of the work. Then again, I thought we allocated the work quite well as everyone was doing what they're good at. This is not to say that I think A- was deserving of the work we had put in. Seriously, considering how much effort this module requires, I think I should have gotten an A in return. But this module is the sort that you put in 10 times more effort than what you get in return. Hopefully there will be some changes to this module for the next batch as I don't think the majority would like to experience what the Year 4s had just gone through.

EC4301 Microeconomic Analysis III

This is supposed to be a level 4000 module. It is also supposed to be a core module initially. Something wrong must have happened midway which caused it to become so unworthy of a level 4000 module in terms of both workload and content. Anyone who has gone through both EC4101 and EC4102 will definitely tell you that EC4101 is nothing compared to EC4102. And true enough, EC4301 is pretty much peanuts compared to EC4302. This module was taken by Chen Yi Chun this semester. And it's not that he can't teach difficult stuff but that he wants to tone down the difficulty due to past bad experiences. He's a pretty good lecturer and I think his lessons are surprisingly not mundane even though the content may be. The module started off hard as we were taught all the abstract stuff in consumer theory. Actually, abstract may be too strong a word for some. It won't actually be if you have been exposed to MA modules. Then when everyone thought they were done for for this module, the lecturer's announcement that midterms and finals weren't gonna test all these proofs came as a huge relief.

Topics
1.   Preference and Utility
2.   Utility-Maximizing Problem and Its Solution
3.   Utility-Maximizing Problem and Expenditure-Minimizing Problem
4.   Law of Demand, Exchange Economies, Pareto Efficiency
5.   Core and Competitive Equilibrium
6.   Welfare Theorems and Existence of Competitive Equilibrium
7.   Choice under Risk
8.   Externality
9.   Asymmetric Information
10. Modelling Strategic Behaviours I
11. Modelling Strategic Behaviours II
12. Incomplete Information and Efficient Mechanism

Weightage

Homework: 20%

Midterms: 30%

Finals: 50%

The homework was given out on a weekly basis and they were to be completed in groups of four or maximum, five. It wasn't graded based on correctness but rather, completeness. So I should expect that no one lost any marks from this component. There was also only one tutorial presentation per group. So the workload for this module was real light.

Midterms was tested up to Topic 5. Topic 6 was covered but not tested and its lecture was conducted during the recess week. Although this topic wasn't compulsory, it turned out to be useful for midterms. If you had attended the lecture or studied the notes on your own, it would help in scoring for your midterms. So take it with a pinch of salt when the lecturer says it's not tested. I disliked the topics after midterms especially Topics 8 and 9. They were way too simplistic for a level 4000 module and it wasn't value-adding in any way especially Asymmetric Information. Up till now, I still haven't been exposed to proper modelling of asymmetric information. All I understand are the implications of asymmetric information. Topics 10 and 11 are on game theory. Topic 12 was centered around mechanism design but its basis came from game theory. Mechanism design was a real interesting topic but too bad, it had to be so brief in this module. I scored 95 for my midterms. Average was 85? I can't recall exactly. The highest was 98 out of 100. I scored 95 probably cos I was pretty good at the first half of this module. Edgeworth Box was covered for Topics 4 and 5 but of course it wasn't as lame as what was taught in EC3101. Then again, I attribute the 95 I got mainly to the lecturer. I actually made many mistakes but he was amazingly lenient with his marking. As long as you showed some understanding of the concepts, he will give you credit. So keep this in mind if you're taking the module under Chen Yi Chun: do not leave anything blank. Actually, midterms was rather insignificant as it was upon 100 and when you convert the marks to 30%, it becomes negligible. The lecturer said it himself that people who scored well for midterms usually didn't score well eventually whereas those who didn't score well for midterms are the ones who fared well eventually. As much as there may be some truth to that statement, I personally think that midterms are such that you should get at least slightly above average if you are looking to get an A- or above. Nonetheless, I don't dispute the fact that finals is the determining factor and my grade is an affirmation of that as well. By the way, both midterms and finals were open-book though it wouldn't have helped much.

It was claimed that finals is cumulative but trust him not. On the whole, finals was easy. I got screwed up thanks to the steep bell curve and mistakes I shouldn't have made at all. As the second part had three chapters on game theory, it was no surprise that there was one entire question dedicated to game theory in the finals. Even though having taken EC3312 may be a plus, it wasn't as much help as I thought. Basically, game theory in this module was a lot more simplistic than in EC3312. Anyway, as with EC2101 and EC3101, the questions in the finals are such that it carries an overly high weightage. For instance, I could be given 10 marks for just a three-liner solution so it was pretty hard to gauge what was required of me especially when certain questions were quite open-ended.

Result: A-

I don't know what to make of this grade. After midterms, I was aiming for an A. After finals, I was realistically expecting a B+. I guess knowing your concepts well is the key to scoring for this module.

EC4303 Econometrics III

First and foremost, this module isn't as difficult as most may imagine it to be. There was more breadth than depth. Honestly, I question the use of econometrics exams at times. Here's the thing. You don't actually have to know how to prove theorems. All you need to understand are the concepts and properties of the theorems as well as how to go about applying them. But unfortunately, and I don't blame the lecturer for this, econometrics exams usually involve quite senseless questions. Anyway, this module was taken by Tatsushi Oka and he takes the definition of politeness to the next level. The topics covered for this module were quite impromptu in the sense that the later topics were chosen only because some of us were doing on these topics for our term paper.

Topics
1.   Ordinary Least Squares Estimation
2.   Linear Probability Model / Maximum Likelihood Estimation
3.   Nonparametric Regression
4.   Quantile Regression
5.   ARMA model
6.   GARCH model
7.   LASSO
8.   Panel Data Models
9.   Program Evaluation I: DID Estimation
10. Program Evaluation II: IV Regression
11. Program Evaluation III: Regression Discontinuity
12. Classification and Regression Tree

Weightage

Problem Sets: 20%
Term Paper and Presentation: 20%
Book Presentation: 10%
Participation: 10%
Finals: 40%

There were 3 problem sets and all of them were easy. They were graded based on effort and correctness. Most people scored 100 or at worst, 99 so this component wasn't gonna make any distinction among the students.

The term paper was to be done in groups of 3. You get to choose your groups. Basically, you had to find an existing paper, replicate the results and extend the paper. There were 2 presentations for this component. The first one was a 5-minutes presentation and it only involved presenting about the existing paper as in the type of dataset etc., the results your group had replicated and lastly, an outline of the extensions. The second one was a 10-minutes presentation and you had to present on the extensions your group had come up with. The report was only limited to 3 pages excluding appendices and all so it was pretty slack. The draft was due sometime during the middle of the semester whereas the final one including probably the last one and a quarter page on extensions was due sometime in Week 12 or 13.

Book presentation. This is probably the one and only useless component of this module. First, we were assigned a textbook, Statistical Learning from a Regression Perspective by Richard Berk and this textbook is considered pretty advanced for undergraduates. All the equations inside weren't what you normally see in an econometrics textbook. Second, this textbook was taught with students making presentations in their groups so every week, there would be one presentation until all 8 presentations were done. The chapter that you present on was decided by drawing lots. So some got the earlier chapters which were easier while those who got the later ones might need to spend a bit of time understanding the earlier ones before they could do their presentation slides. The presentation was up to 25 minutes and all 3 group members would present a section. I think during this weekly presentation, everyone was just shutting off their ears and that included me. The thing is some presentations were so poor that you could tell they didn't really understand the content themselves which I perfectly understand why. I really question the use of this component as the presentations not only consumed time but also, the book chosen is a bit too advanced for self-studying as its content is very different from what you usually see in econometrics.

Don't worry about the component on participation. You can get it just by attending all the lessons.

I actually only realized finals is 40% as I typed the weightage. But finals is the determining factor to your grade for this module. Oka was very generous with the 60% CA component as he said that everyone would probably get full credit for it. Finals was open book and there were some questions that we could directly refer to assignment solutions or lecture notes to get the marks. Then again, I thought the differentiating factor came in in the last 2 questions which added up to a total of 16 marks. I probably screwed up more than half of that 16 marks but judging from my grade, I believe most people did as well.

Result: A
This grade came as a big surprise as I was expecting at most an A-. Even though this module was more of breadth and it was a lot less rigorous than I thought, I think it's pretty much a must-take if you're looking to go into specialized economics jobs. Anyway, knowing more econometrics models is always a good thing for someone studying economics. This is not to say that you should take it if you're afraid of screwing up your CAP. I think I just managed to scrape through an A as it was really competitive with the cohort size of 20.

AY2014-2015 Semester 2 Module Review

I finally have some time to sit down and start writing this. The reason being I've been given a lot of work from Dr. Song whom I've been working as a research assistant for for the past one year or so. And on top of that, I've been working out a general direction to my thesis with my supervisor. You're probably wondering why I'm starting so early. That's just cos' I'm intending to overload to 30 MCs next semester. So it helps to spread out the workload a bit. Now you think that all sounds good but the fact is I'm only in the preliminary stage of finalizing my scope.

Now, back on topic.

Basically, I did only average this semester. And until now, I'm still not sure where I have gone wrong for two out of my four core modules. So this time round, I'm gonna take a different approach to my module review instead of my usual practice of following alphabetical order and starting with EC.

I'll first talk about the most unimportant module and that is SSA2211, a module which I can literally count with my fingers the number of hours I've spent on it in the entire semester. Then I'll move on to talk about the two modules that I've screwed up and which I do not know the exact reasons for why I did. So the disclaimer is that what I will say might turn out to be quite subjective. Finally, of course comes the two remaining modules that I know why I've screwed up or done well.

To sum up, the order of my module review will be the following: SSA2211, ST3242, ST3247, ST3239, EC4332.

SSA2211 The Evolution of a Global-City State

I would say that if you are someone who likes to think of already-defined history from a different perspective, then this module is definitely one for you. Norm has it that Singapore's history begins with Raffles' arrival or ok, maybe Sang Nila Utama. But this module takes you back to the 14th century and tries to argue why Singapore's history should be defined from that period onwards. Or at least I felt that was for the most part of the module. Then subsequently, the module unfolded according to the timeline on Singapore, moving onto Singapore's interaction with the Malay world and then onto the modern history and so on.

Personally, I find that as much as I was not the least interested in this module, I must say that it's quite an avenue to invoke your thinking to some extent. It makes you think of things in a way that you wouldn't have thought of. It's not your straightforward SS module or what you might have expected it to be. So if you're really keen on this module, chances are you'll enjoy it.

Workload wise, it wasn't too heavy or maybe because I didn't put effort into it.

Weightage
Tutorial attendance and participation: 20%
CA1: 20%
CA2: 20%
Finals: 40%

As typical of all arts modules, the first component wouldn't be easy to secure if you hadn't participated in tutorials. I, for one, chose to take this module because I saw that we'll only have four tutorials in total and that one of them was e-learning. Moreover, I missed one of them as well though I had a valid MC. So it's like my goodness, the last tutorial was the second and also the last time I was meeting the class. And of course, I did not participate at all so I'm pretty sure I lost at least half of this component. On another note, I am making an objective viewpoint by saying the tutorials are useless. Really, I think that the debate on the IVLE forum made so much more intellectual sense than the tutorials. Or maybe it was because my tutorial group was a bit passive to begin with and my tutor didn't seem to have much experience which explains why there weren't any insightful points raised during class. I'm not saying I read what people wrote on the forum because the truth is I didn't. In fact, I only knew the forum is active because I subscribed to it. But I did scan through the first few lines of the post when I received the email from IVLE. This was sufficient enough to give me an idea of what the post was roughly about so I can safely say it's a lot better to engage in the online discussions rather than the tutorials.

The second component comprises of an MCQ component and two structured-questions component if I may put it in my own words. The former made up 20% while the latter, 80%. And the 20% is free. I do mean free. Because you get to have a total of two tries for that component and after the first try on IVLE, they'll actually point out your mistakes and tell you the right answers. Oh yes, I didn't type that wrong. It was stupid but I guess in some way meaningful because that 20% was there to help you for the 80%. You basically get a clearer direction as to how you should answer the two questions for the 80% with those answers you got from the MCQ.

I finished this task just before the deadline which was the Sunday of the week of CNY. So you had to complete this by 2359 before it turns Monday. And after a delighted week of slacking, I was rushing this damn thing and finished it under 3 hours when it was recommended that we start two weeks ago when the assessment was released. Right but that came with a price as I only got a mere 72 out of 100. Most people were in the 70s range by the way so that essentially put me in the B range already.

Then came the second component which was due on the Monday of Week 12 if I didn't remember wrongly. Oh did I mention that this module advocates short and sweet instead of long and "detailed"? This was an essay component where you had to choose to stand in the shoes of one of the following: a Peranakan trader or merchant I can't remember, someone from a... Ok forget it. I have the full question paper so for those who are interested, you can get it from me. So you had to make references and stuff and was limited to 500 words I think. Oh but heck, I once again rushed this on the night before. As to the grade I got, I never knew as I was too lazy to go back on the Week 13 Friday to collect this back. But I do know from my tutor that I did ok. So I guess it was average.

And finally, finals. I read the notes for 2 hours or less and went to sleep in preparation for my first exam of the semester but I didn't feel like my exams have started cos I knew I was sitting for a module that I'm gonna have to use my S/U for. You'll be given a timeline of events in the exam that briefly touches on what has happened over the many centuries. Well, it'll be useless if you hadn't studied cos you wouldn't be able to make much sense of it like what I experienced. So I was just staring at the questions and deciding which one I could recall the most information for.

Result: B- (S)
Disappointed. I expected a B. But B or B-, still an S eventually. All I have to say for anyone who wants to take this module is that it's no use doing rote learning. Besides familiarizing yourself with the facts, it is also equally, if not more, important to begin questioning yourself and thinking more deeply into the issues. And one tip is that there're always some questions at the start of each tutorial. I mean they're printed on the tutorial itself. So print them out and start answering them. They'll serve as a very good preparation for finals.

ST3242 Introduction to Survival Analysis

This module was taken by Anthony Kuk. And he has improved greatly from when I took ST3131. But that still didn't stop me from not attending lectures. Tutorials are combined with lectures. So instead of two 2-hour lectures each week, it went down to one 2-hour lecture plus one 1-hour lecture plus one 1-hour tutorial. That also means the tutorial was personally conducted by the lecturer. Lectures weren't webcast but I think his notes were detailed enough.

I really kinda like this module a lot as much as I'm disappointed with the final grade. If I were to draw a similarity to a foundational module, I would say this module is most like ST2132. ST2131 only came in in one of the last few chapters and in the form of moment-generating functions and iterated expectations so it was a very small part. But the thinking was most similar to ST2132. It involved MLE and all. There was a lot on MLE but it wasn't just MLE alone. When it got to the semiparametric Cox model, it was more of computation of rank likelihood. Basically, I guess you could say that this module focuses a lot on how you would model survival data. Maybe model is too strong a word for technical dudes. I guess you can say it touches mostly on regression, or along that line. The thinking is very similar. I mean when we do regression, we think of whether the assumptions of OLS, to take the simplest case, are satisfied and what the solutions are if they aren't. A similar thing is done in this module. For example, in applying Cox's model, we assume proportional hazards. But what do we do if the assumption is violated? Also, you sort of see the realism in this module where we separate out different groups of individuals into stratas and assign a unique characteristic to them before carrying out analysis in R. And talking about R, this module uses a lot of R such that you begin questioning the presence of certain topics with regards to examination purposes. Then again, that's what makes the module more realistic. You take the data to a software, look at the coefficients and begin thinking bout' its implications for your model. 

Weightage

Assignments: 20%

Midterms: 20%

Finals: 60%

There were two assignments, one before recess week and one before reading week. The assignments were very easy to score. I got full marks for both of them along with some 95% of the cohort so that tells you a lot. 

Midterms was really easy too. I thought it was a test of time and accuracy rather than knowledge as everything was just straight from the notes. It also helps that it's open-book. I got 59/60 with 1 mark lost because I did not simplify something. But I think there was a total of 8 or 10 people who got 59 or 60. The median was around 43, very much to my surprise. I think a lot of it was due to carelessness.

The finals was also open-book but it was obviously a lot more challenging compared to the assignments and midterms. It required thinking and good understanding of concepts. There were altogether 5 questions and each was worth 20 marks. Only one of them was a blatant giveaway. 

Result: B+

I was extremely disappointed with this grade. I thought I did fairly well for the finals but apparently, I did not. It was weird because I could answer questions that others couldn't but I made mistakes in the last question which was probably the one that cost me my grade. Plus, maybe the proof that I gave in the first question wasn't foolproof enough. Well, so this is one of the modules I had no idea why I scored this way. Up till now, if you ask me, I still can't give an answer. I'm actually quite curious myself because I tend to reflect on why I did badly for a particular module and up until before this semester, I could always give myself the answer but this time round, I really can't. 

I guess maybe there were a whole lot of others who found the paper manageable or even easy. I can't say that this paper was hard but I definitely wouldn't say it was easy either. Before the results came out, I was realistically expecting an A- for this module but turns out it was even worse than what I thought.

But what I suggest is not to take the concepts at face value. Rather, try and look deeper and start appreciating them and their applications etc. All in all, I did not regret taking this module as it was interesting and for anyone intending to specialize in Biostatistics, taking ST3242 is sort of a must.

ST3247 Simulation

Once again, this is another module that I am truly disappointed with the final grade. It was taken by Vik Gopal. He's one hell of a good lecturer cos' he's always so patient and explains things very well. Probably the only issues with him are that he might be slower in replying emails and to me, it was as if he was rushing through some of the topics which I thought he might as well use the freed-up Week 13 so as to go slower on the earlier topics. Then again, it's probably because I'm very slow as it was only the weaker ones who weren't able to follow him. That said, I did not attend both lectures and tutorials for this module. Lectures were webcast so it's okay. If you do not attend lectures, watching the webcasts is a must as there may be quite a bit of important information passed down during lectures; things like how you should answer a certain question. And you could find yourself staring blankly at the notes without the explanations given during lectures.

I regretted not attending the tutorials. The reason being I was really so slack the past semester that I had trouble keeping up with the tutorials. So it became a snowball such that when the class could already be at say, tutorial 5 during Week 8 and I was only at tutorial 3 at most. It was really bad. To digress a bit, I think I owe my laziness to the lack of breaks from the start of last Semester 1 until the end of Semester 2. As I had to do an internship right after the end of finals of Semester 1 and only ended it before the start of Semester 2, I really lacked a break in between. To make things worse, Semester 1 was already pretty physically taxing on me as I often had to stay up late in order to finish up the work on my RA side. And I have neither the mental capability nor the discipline to pick up a pen and start doing work this semester. But really, the tutorials were useful in my opinion as there were some questions in which you really needed an explanation from the lecturer. Oh, I did attend the very first tutorial and Vik provides extra insights into the more challenging questions which makes you understand better. 

And again, if I were to draw a similarity between this module and a foundational module, it would most definitely be ST2131. If you're not good at ST2131 and do not want to screw up your CAP, then avoid this module. I was not good at ST2131 but I decided that this module was gonna be useful. It first started out with how one can simulate a random variable from discrete and continuous distributions. This part of the module was hard for me because I wasn't good at my foundations from ST2131 so most of the time, I find the methods that Vik's teaching very out of the blue. It's like I would never think of such hoo-ha methods. Then came monte carlo and after Week 7, it was my favourite and most challenging part of the module, discrete event simulations. So everything you learnt bout' simulating from distributions comes into play. You're given a real-life situation. For example, the classic one used in this module is that there's only a single server at say, a bank. So you had to find out the arrival time, waiting time and departure time of each customer. To take it to a more complex level, the customers would leave after a certain waiting time according to a distribution you have to simulate from as well. Nevertheless, all these are already very simplistic scenarios.

Weightage

Assignments: 20%

Midterms: 30%

Finals: 50%

There were 4 assignments in total. You had to submit two portions; one was the handwritten portion to be submitted to the office and another was the coding portion to be submitted on IVLE. The first two assignments had both portions. The third assignment had only the R coding portion while the last had only the handwritten portion. I got full marks for all the assignments but of course, that didn't help at all in pulling up my disastrous midterms. Nonetheless, try not to lose marks in the assignments even though the median is always not near the full mark. I mean the first two assignments were kinda hard but the last two were easy. Then again, all the assignments took up a lot of my time except for the last one on validation techniques.

Midterms was upon 40. And I can say I did not do well because I did not study hard enough. I do mean it. Because I went home to try the questions again and I easily scored above 30 instead of the mere 25 that I actually got. The median was 22. At that time, I slacked too much especially due to the festive CNY season. So I was rushing through all the tutorials before the midterms. I thought I understood them and I neglected non-homogeneous poisson process which so very well came out in the midterms. It was easy but I lost the marks due to complete ignorance of that concept. 

I was hoping finals will be hard with emphasis placed on discrete event simulations as I had practised quite a number of challenging questions from the textbook and was confident that this would be the topic which can pull my grade up. How dismayed was I when I saw that not only was the DES question easy, it was taken straight from the past-year paper as well. In fact, the paper was so easy that 1/3 of the cohort left before the one and a half hour mark.

Anyway, it's kinda strange; closed-book, no cheatsheets, no formula sheet. I mean there were really quite a lot of algorithms to remember coupled with its details. And that's just the part on algorithms. There were still some other formulas to remember for the later topics. Right, talking bout' algorithms, the emphasis of this module is on pseudo-code so you do not need to be well-versed in R in order to obtain a good grade. That said, if you wanna take it to reality, of course you gotta show a certain level of competency in R so as to make use of whatever you learnt in this module. Nonetheless, there's sufficient guidance from Vik to ensure that you can code whatever you were taught.

Result: B

I was expecting a B+ and I've got no other reason for why I got this grade except that the bell curve was too steep thanks to the finals. I can say this with certainty because Vik sent the review of the finals to us after he finished marking and I got everything that he pointed out as a common mistake right. I mean I really spent time to understand the concepts towards the end of the semester. But there was this question on alias method that I totally missed out a formula which cost me 4 marks and I believe that was the contributing factor to my grade on top of the mediocre performance for midterms. 

Even so, I do not regret having taken this module. I really enjoyed the part on DES and the flow was great because you could make sense of what was required given a real-life problem. You had to know how to simulate from distributions, apply it to discrete event problems then perform checks as to whether what you had assumed for the problems were right plus whether the results you got made sense in reality.

ST3239 Survey Methodology

This module was taken by Zhou Wang. You may have some difficulty understanding what he's saying due to his accent. For the record, I did not attend any lectures except for the first. Lectures weren't webcast. You might lose out a bit provided you can actually follow him during lectures. Anyway, he uploads the notes shown on the visualizer in lectures.

Different sampling methods such as simple random sampling, stratified random sampling and cluster sampling are among the topics that were covered. The only topics that may sound more foreign are ratio, regression and difference estimation as well as estimation of population size.

I can say without hesitation that ST3239 is definitely one module that I regretted taking. I gave bulk of my bid points to it in the hope that I would score well due to its similarity to ST2132. But not only did I not score well, it was not the least useful to me unlike ST3247. And I didn't find it interesting like ST3242. If there is one word that I need to use to summarize the content from this module, it would be "proofs". Lots and lots of proofs were provided. But it wasn't the focus of this module I guess. You know the thing is that most people do not follow theory when they do sampling. I don't know if it's because they're unaware of the implications of not doing so or whether the implications of not doing so are too blown up thanks to advocators of sampling methods. I'm saying this because I recently had to code block randomization in Stata as a task given by my RA Prof. And I tried to argue with him that doing the way he told me to would result in biased estimates. But the answer he gave was that as long as we perform a t-test and the p-value is high, it wouldn't matter much for a large sample. In fact, before I took this module, I will not think that I would ever have to use the knowledge I'll be getting out of this module in years to come. I mean I'm not gonna go into something that requires empirical work, not even for my thesis. And even if I do, it seems like EC people are kinda too, if I may put it bluntly, ignorant to even know about the existence of such theoretically-validated methods. Even so, it might not come to me as a surprise if anyone who has taken this module realizes that it's sorta unrealistic. But to be fair, for anyone who would like to work in fields related to empirical research, it's probably good to take this module.

Weightage
Tutorial attendance: 10%
Assignment: 30%
Finals: 60%

I've to say the workload of this module is really light. You just have to attend a total of 5 tutorials in the span of the entire semester to get full credit for the first component. As for the second component, it was actually meant to be a midterms but for some reason or another, it was decided that the midterms be changed to an assignment. The assignment was extremely easy which resulted in the median being 94 out of 100. I got 96 which was only at most a B+ grade. The finals was, as I mentioned in my previous post, extremely easy. Basically, this module was mostly just applying formulas from the notes. Nothing fanciful at all. In fact, everyone found it to be one of the easiest level 3000 electives.

Result: B+
I attribute the grade I got to the 20 marks I lost on the question in the finals which actually only required clear-cut copying from the notes. So if you had copied the proof one-for-one onto your cheatsheet, you'll be able to get full credit for that question. Besides, the lecturer did mention that the paper was found to be easy for most people but of course, it wasn't as well done as the assignment due to carelessness but it still doesn't change the fact that the bell curve will be really very steep. Nonetheless, the lecturer also said that there wasn't sufficient understanding of the notes so this may serve as a tip for anyone who wishes to take this module under Zhou Wang.

EC4332 Money and Banking II

I think the title "Money and Banking" isn't reflective of the content covered for this module if Martin Bodenstein is the one taking it. Instead, he geared the module towards monetary policy such that there wasn't much of banking at all. Nonetheless, he has very good understanding of the material he's teaching. I guess this is because of his work experience. You can look up his CV for what I mean. By the way, he's all good and well face-to-face but not when it comes to emails. He replies to an email once in a blue moon so most of the time, he doesn't. Anyway, if you find yourself interested in what I'm gonna say below, take EC4331 Monetary Economics and Policy next semester. According to him, it's because the EC department wants to move EC4332 back to the more qualitative line of content such that it'll be more of a build-up from EC3332 so they decided to create a separate module that focuses on monetary policy. And, for anyone who wants to specialize in monetary economics, this module is a must-take. I find myself reading papers on monetary policy with ease now as compared to when I first started back in Feb whereby there was nothing then that I could understand.

The New Keynesian Model is one of the most widely used models in analyses of monetary policies. And even if the papers you're reading happen to not be using NKM, chances are that once you study NKM, you'll find yourself equipped with the ability to understand most of the other models as well because the current trend is that most models are built on microfoundations just like the NKM. You can get a little bit of the NKM from EC4102 under Aamir Hashmi. But of course, it's not as full-blown as this. Speaking of EC4102, it'll be highly advantageous to have taken EC4102 before you take EC4331. Although EC4102 is a co-requisite for EC4331, I do think the relevance to EC4331 comes in only at the last bit of EC4102. This means it'll be better to have taken EC4102 before you take EC4331.

This module starts out difficult due to the sheer amount of so-called algebra such that you begin seeing stars in the third homework or something. But in the lecturer's own words, all the algebra you do in this module are trivial. What's more important is that you get the intuition of why a particular shock will change the economy in the way it did. In fact, that is also the most difficult part of the module for me: intuition. Until now, if you ask me, I may not be able to give a very satisfactory answer to some of the qualitative questions covered in this module. The lecturer probably recognized that and set the finals such that it focused a lot on qualitative understanding rather than quantitative understanding like in the midterms. And halfway through the semester, I started spending much less time on this module as there was really nothing much you can study. Well, but I guess the homework helps to keep up consistency.

Weightage
Tutorial attendance and participation: 10%
Homework: 20%
Midterms: 35%
Finals 35%

I do not know why the first component even exists in the first place cos' even if there were people who went up to present during tutorials, their names weren't taken down. But the lecturer did mention that everyone will probably get full credit for this component.

Each person was allocated 4 homework in total. How it works is that there were altogether 10 homework. And everyone would be assigned 2 among the first five and the remaining 2 among the last five. Of course, this once again comes with some sort of bias. I got allocated the more computationally intensive ones which seemingly, a lot of people had difficulty with. The last 5 homework were all fairly easy whereas the earlier ones were very time-consuming; I can spend up to 4 or 5 hours just to get them done. I got full marks for only one assignment whereas the others were all 9.5 out of 10. I guess it was already somewhat disadvantageous as some got full marks for all. Nonetheless, I don't think it matters much as long as you didn't get like 6 or something.

Midterms was quantitative in nature. There were 3 questions in total. It wasn't a test of difficulty but time. The first question was algebraically intensive and that took away 55 minutes out of the two hours we had but even past the one-hour mark, there were still a lot of people struggling to finish the first question. I got 95 out of 120. The median was 82.

And lastly, the killer finals. I must say, and I said this to the lecturer himself, this is without doubt the hardest EC paper I have sat for by far and I hope it'll be the hardest one already. Apparently, he said that he deliberately phrased the questions in a way such that if you do not know your concepts well, you wouldn't know what he's asking for. Basically, the finals was a test of conceptual understanding. There were two questions and I could do the first one with confidence. But I lost it halfway through the second one because there came up some weird variance which I've never seen before in the entire semester. And by the time I figured out what the variance meant, I could only do the 5 marks proving and not the 10 marks one. Most people around me either gave up or were panicking as well. It doesn't help that this is not the kind of paper whereby you could just move on to the next part if you did not know how to do the previous because it was a snowball which summed up to some 30 marks out of 120.

Result: A+
I was very pleasantly surprised by the result. Never in my wildest dreams did I expect to get even an A-, much less an A+. I've no idea how and why I got this grade. Seriously, I don't think I deserve the grade at all because in absolute terms, I actually didn't do well for the paper especially for the second question. I guess I got the grade only because I did well relative to others. In fact, the lecturer did mention in his email to us after grading the finals that our performance for the finals was a little worse than what he expected. This reminds me, many people have said that level 4000 modules have no bell curve. But I'm pretty damn sure that this module has and this on top of the small cohort size of 34 students just goes to show how intense the competition had been. With so many factors in play, it really got me wondering how I got this grade but I never figured out, not until I met the lecturer sometime later...

So he told me it's because I demonstrated very good understanding of my concepts in the finals. And there was apparently a very huge gap between me and the second best scorer; I do believe that the second best scorer was probably the one who got 102 for the midterms and 102 was the highest mark for the midterms. In fact, the 95 I got was only around the 75th percentile benchmark which essentially put me in the A- range already. I guess for anyone who wants to take EC4331, be prepared for a challenging finals though I highly doubt the finals will be as hard as this semester's from what I was told. However, if you know your concepts well, chances are you'll be able to do well for this module as the lecturer also mentioned that most people can follow the notes and keep blindly applying the method of undetermined coefficients, but then how many of them actually understand what they're doing? And before I forget, do not attempt to write long-winded solutions for the qualitative questions. I did so for one of the homework and I was deducted half a mark for that. It's preferable that the answers be short and straight to the point. Probably that was one of the contributing factors to my grade for finals.


And that's it for my module review this semester. By the way, I did not give a list of topics covered for each module this time round. But I do have the full set of lecture notes, assignments etc. for all my 4 core modules. However, I'm no longer gonna upload my stuff and I've my own reasons for doing so. So if you would like to get access to my course materials, drop a comment along with your email address and I'll try to respond asap.

Update on AY2014-15 Semester 2 Module Review

Sorry to disappoint but my module review this time round won't be up so soon. 

Then again, it's summer holidays so fret not as you guys won't have to decide on your modules anytime soon. Nonetheless, I should think that it'll be up before FASS starts MPE. The reason is because I have been and will be very occupied this week and many more weeks to come. 

And due to some surprises, both good and bad, about my results, it's gonna be quite difficult to write my module review objectively. So simply put, I need more time to do up a good one for this semester.

But in case there are readers out there who's very eager to know what any of the modules I've taken last semester is about, feel free to leave a comment in the chatbox and I'll reply you asap.

AY2014-2015 Semester 1 Module Review

I am so relieved to have overloaded this semester and cleared 6 core modules at one go as I just realized my schedule will only be getting increasingly more hectic in the remaining semesters. On one hand, the modules I intend to take in the subsequent semesters are a lot more difficult and time-consuming and on the other hand, having to juggle work on top of studies and meeting the deadlines set by the professor isn't something easy for me.

But anyway, this semester wasn't as tiring as I had imagined it to be. Rather, I thought it served its purpose of preparing me for even tougher semesters ahead. Nonetheless, I am contented with my SAP this time round and hope to be able to maintain such results for the rest of my candidature.

EC3304 Econometrics II

This module was taken by Eric Fesselmeyer. I thought he had poor planning in the sense that he spent almost 3 lectures only to cover the first chapter which was basically just a review on the concepts taught in EC3303. After he came to realize how much time he had left before the midterms, he started to rush through the next two chapters so that he can include both of them in the midterms as well. And when midterms was over, he took his time on the following chapter only to rush through the last two chapters again. In fact, he cancelled the lecture in Week 11 or so and made up for it with a webcast that I guess exceeded the usual 1 hour 35 minutes (I am guessing as I did not watch it). If he had not done so, there was probably no way he could have finished what he wanted to test by Week 13. What's more the syllabus he showed during the start of the semester included one more chapter on "Quasi Experiments" but due to the lack of time...  By the way, there wasn't even a tutorial on the last chapter.

Anyway, I don't think there's a need to recommend whether you should get the textbook as chances are you might already be holding onto it considering that it's the same textbook used for EC3303.

Topics covered before midterms
Review
Introduction to Time Series Regression and Forecasting (Chapter 14 of the textbook)
Dynamic Causal Effects (Chapter 15 of the textbook)

Topics covered after midterms
Cointegration (part of Chapter 16 of the textbook)
Panel Data (Chapter 10 of the textbook)
Regression with Binary Dependent Variable (Chapter 11 of the textbook)
Instrumental Variables Regression (Chapter 12 of the textbook)

I have to say the proofs that Eric does during lectures are a lot clearer than those in the textbook. And yes, proofs are important as there was one 35-marks proving question in the finals which was the differentiator. And well, he said things that he showed using the visualizer which include the proofs will not be in the webcast but apparently, he doesn't have a good idea of how the webcast works so I actually skipped the lectures after the fourth one and I'll watch the webcast just for the part on proofs cos' other than that, the lectures are pretty much useless.

The workload for this module is very light as tutorials are not weekly but fortnightly instead. His tutorials include application questions that require the use of Stata and I personally think that these questions shouldn't be neglected. There are questions in his papers that will show students the output from Stata and answers will have to be inferred from there. But the point is these questions will give you a good idea of how the concepts learnt in class can actually be applied in real life and you tend to better appreciate this module after doing them.

Weightage
Tutorial attendance and participation: 20%
Midterms: 30%
Finals: 50%

I thought the first component was absurd cos' this module only has 5 tutorials and you have to present just once. Most people will be very 'enthusiastic' in presenting the solutions for the first few theoretical questions but when it came to those questions on Stata, there would be a sudden silence in the class. So I would think that it'll be good to prepare those questions at the back so that you'll get your chance to present. My tutor, though very approachable, can't teach for nuts and yes, I seldom say that so the tutor has to be really quite bad. I would have loved to skip the tutorials if I could as it wasn't value-adding in any way. Due to some reason or another, I did not attend one of the tutorials and even though I went for the makeup in the odd week, my tutor actually forgot to mark my attendance so that I had to go to Eric personally but now I've doubts as to whether he marked my attendance for that week as well.

Ironically, the emphasis in midterms was on stuff covered in EC3303 and I honestly do not admire the questions set by Eric or probably that's because I've taken ST3131. Specifically, there are 3 questions on the 'Review' part and 2 questions on 'Time Series'. So if you are good at the stuff in EC3303, you'll probably do well for the midterms though if you suck at the subsequent chapters, chances are you'll still screw up the module eventually. I do know of someone doing very badly (way below average) for the midterms but still got away with a decent grade and also, another person doing very well (way above average) for the midterms but got a not-too-decent grade eventually. Median was, if I did not remember wrongly, 63/100. I got 73 which was exactly the 75th percentile. Anyway, Eric takes a pretty long time to mark the papers; the papers will be ready for collection at the general office probably two weeks after the midterms.

There were 4 MCQ questions in the finals and each was worth 5 marks. I got the first question wrong which I believe could be the contributing factor to my grade on top of the tutorial attendance issue. But really, finals was manageable; just know what you are doing and you should have no problem in scoring well. In fact, the last question on 'Binary Dependent Variable' was a giveaway provided that you made no careless mistakes.

Result: A-
This was one disappointing module as I was hoping for an A. But overall, I did enjoy this module to some extent as the concepts covered were pretty relevant (though simplistic).

EC3332 Money and Banking I

This module was taken by Seet Min Kok who is a new professor. He is very helpful as he will answer your queries very promptly. I did not attend his lectures at all (not even the first one) as his notes are just a summary of what's covered in the textbook. In fact, I did not print any notes too; I just used them as a guide to what's covered in this module. And one thing about this module is that there are too many assumptions behind the concepts and when I asked the lecturer about them, there are times which he had to agree with me or that he couldn't give me a satisfactory answer. 

I recommend getting the textbook as it is a lot more detailed. Well, I was told by the lecturer to get the 10th edition as he will take questions from the textbook for the tutorials and so I stupidly heeded his advice and bought the expensive book only to see that I can count with one hand the number of tutorial questions he referred the students to the textbook. Anyway, I am not going to list the topics covered in this module as it is very long and more importantly, the syllabus is already written very clearly in the IVLE workbin. I actually think that taking this module with EC2102 will give you a bit of an advantage as there is some overlap.

Weightage

Tutorial attendance and participation: 20%

Midterms: 30%

Finals: 50%

As usual, the first component is absurd though not as bad as EC3304 since the tutorials for this module are on a weekly basis. I think your participation marks is contingent on which tutor you get. For my tutor, I participated only like 3 or 4 times and he mentioned he was very generous with participation marks so he usually gives every student full credit.

Midterms was one of the stupidest papers I have taken in NUS. Yes, strong word: 'stupidest'. Why? Because it is a 30-MCQ paper which tests you on memory and basic concepts. So if you did not read the textbook properly, chances are you'll not do well like me as I only got 25/30 and most people got 27. Well, I could have gotten 26 if I did not misread one question but 26 is still bad enough as that means 4% is instantly gone. At that point in time, I thought the bell curve was insanely steep as this module was really a breeze-through such that if I needed a break from my other modules, I would read this module's textbook for leisure.

Finals was again really easy; there were 7 structured questions and I am guessing you can answer them at any length you wish as students are given a booklet. Some people left early so that's quite indicative of how fast you can finish the paper if you wish. There were even a few questions which was directly taken from what's covered in the notes and textbook. I felt like this was a paper of "who can explain better" rather than "I know my stuff better than you". 

Result: A

I was taken aback by the result so apparently, I might have overestimated the bell curve quite a bit as I was expecting at most a B+. But I was one of those people who did not have free time on hand during the finals as I answered every question in a detailed manner; listing down all the assumptions, explaining how the theory came about, etc. I actually recommend doing that because most people found the finals an easy feat so it was not about whether you can do the question and from my grade, I think finals will still be able to make a difference if you take the paper seriously as much as the questions make you not want to.

EC4102 Macroeconomic Analysis III

This is easily one of my favourite EC modules so far simply because of the introduction of mathematical concepts into the content despite these concepts being very easy, perhaps not even reaching that of a level-1000 MA module. I suggest that instead of figuring out the integral and summation signs around, I think time will be better spent on appreciating the concepts behind the equations. And rumour has it that EC4102 is the hardest EC module around but I can say for sure that the difficulty level is really not like what people make it out to be. It might start out hard or at least it did for me but as you get more comfortable with the content, you'll find the subsequent chapters becoming increasingly easier. The only difficult thing is probably the mere number of people taking this module and the fact that only honours students are left cuts down a lot more leeway. Although this is supposed to be a macroeconomics module, there is extensive use of microeconomics in getting the macroeconomic picture. They term this as 'microfoundations'. Basically, you have to analyze the behaviour of consumers and firms in order to derive the performance of the economy as a whole.

This module was taken by Aamir Hashmi. He is a very good lecturer face-to-face. By that, I mean if you look for him to ask questions, the amount of patience and clarity he has for you is wonderful but you might be slightly put off by the replies he gives if you're talking about emails. Anyway, there are times when students ask him questions and he'll be like "I don't actually know the answer to your question". I actually like his honesty as I've met some professors who smoke their way through students, thinking students would actually believe them. 

The textbook for this module is 'Advanced Macroeconomics (4th Edition)' by Romer. I strongly recommend getting the textbook for this module despite it costing a bomb. For frugal people like me, I believe you do know that there is some way or another to get the textbook without purchasing it. Perks of doing so are the larger font size and more importantly, the ample space for scribbling. But some people might think that his notes are good enough. In fact, I do think that for some chapters, his notes are even better than the textbook. As for tutorials, even though the questions are taken from the textbook, he will also upload them onto IVLE. By the way, given that this is a seminar-style class, tutorials are not given out systematically. Instead, only when Aamir thinks that he has finished what should be done will he upload the relevant tutorial questions. 

Topics 

Ramsey-Cass-Koopmans Model (Chapter 2 of the textbook)

Overlapping Generations Model (Chapter 2 of the textbook)

Endogenous Growth Model (Chapter 3 of the textbook)

Romer's Model (separate paper will be uploaded)

Real-Business-Cycle Theory (Chapter 5 of the textbook)

New Keynesian Models of Incomplete Nominal Adjustment (Chapter 6 of the textbook)

Dynamic Models of Incomplete Nominal Adjustment (Chapter 7 of the textbook)

Well, I guess the good news is that the finals is toned down a lot after 'live feedback' from students several semesters ago whereby there were some people who cried while walking out of the examination hall. I actually enjoyed the past papers Aamir set as it makes you feel that this is indeed worthy of a level-4000 module. 

Weightage
Tutorial attendance: 10%
Midterms: 30%
Project: 20%
Finals: 40%

The first component is free as long as you attend all the tutorials. Midterms was disappointingly easy; anyone can score well if they don't make careless mistakes (though it's pretty hard to) and have studied for the test. How the grading works is that everyone's marks will be standardized and you'll get a grade accordingly. Highest was full marks and average should be around 23/30. I got 27 together with nine or ten other people. He'll upload everyone's scores in a PDF file within a week after the midterms so that speaks quite a lot about his efficiency.

Without a doubt, the stupidest component of this module has to be the project. Basically, every group gets to draw a paper and the task is to come up with a 1000-word non-technical summary on the paper you've drawn. This is worth 15%. Then there is also a 10-minute presentation which makes up 5% of your grade. Not everyone presents at the same time though as it depends on which paper you get. The presentations are spread out over the last three weeks of school. The bell curve for this component is really steep but the unfair bit is that if you get an easy paper like I did, he will mark you more strictly. One thing to note is when he says non-technical, he really means it. Anyway, he turned this component into a summary because he released a freestyle topic when he first took this module whereby students just have to sieve out articles and apply the concepts learnt in this module. However, it was somehow too difficult and so Aamir decided to remove it and change it to something at the other end of the spectrum.

Finals was non-cumulative but was again too easy; straight from textbook, simple manipulation... You name it, you have it. While the median used to be a failing mark in the past few semesters that he took the module, I think the median for this semester should be pretty close to the full mark. Aamir claims that if you do sufficiently well and he feels that you deserve the grade, he'll give it to you. Nevertheless, I may have overstated the ease of the finals as I know of people who lost over 10 marks in the finals and still got away with a decent grade.

Result: A
I was expecting an A- since I screwed up the project component and even though I believe I should have gotten close to full marks for finals, I'm quite sure everyone else did too. I think it is important to attempt all the derivations again before the finals and ensure that there is no room for careless mistakes during the finals.

MA2311 Techniques in Advanced Calculus

Stats majors get to choose to take either this module or MA2108. I personally think that this module will be more useful for Stats majors as it is important to know multivariate calculus. And this module makes it simple enough such that it does not improve any proving as things like Green's Theorem wasn't introduced plus there is no vector calculus. So only computation of multiple integrals will be tested. Besides, the focus of MA2108 is unnecessarily abstract for Stats majors. But if you have talent for that and you're in need for a CAP puller, then take MA2108 by all means. Nonetheless, because MA2311 is the only opportunity for Stats majors to be formally exposed to multivariate calculus unlike for Maths majors, I still hold on to my stance. Anyway, there could be certain Stats electives that may require double or triple integrals (though I don't see them being offered anymore).

This module was taken by Ji Feng. He is excellent, period. Firstly, he is one heck of a good teacher; his lectures are wonderfully conducted as he will take time to write down the steps for his examples on the board. Secondly, he is really helpful; he can get back to you within 15 minutes of your email 99.9% of the time. Thirdly, I had him as my tutor as well and he is very clear in all his explanations. Fourthly, the syllabus for the entire semester was very well-organized in the sense that he could keep a steady pace throughout the semester and still managed to keep Week 13 free. Lastly, his lecture notes have sufficient examples and on top of that, there is often additional information provided during lectures. Lectures aren't webcast by the way.

Topics

Sequences

Series

Vectors

Functions of Several Variables

Multiple Integrals

In terms of quantity, this module is really slack but in terms of quality, maybe it's because I'm not inclined towards the subject but I actually spent a considerable amount of time on this module though I began to neglect it after Week 10. Nonetheless, because this module precludes those who took MA1505 or MA1104, it cuts down the competition by more than half already. However, I must say that the papers set for this module would be an eye-opener if one simply took the tutorials as a gauge to the level of difficulty of this module.

Anyway, there is no textbook for this module though I would recommend 'Thomas' Calculus' or 'Calculus' by James Stewart. I think either one of them should be the same as the textbook used for MA1102R. In terms of content, I think it's pretty redundant to refer to the textbook as the notes are good enough. But I think there are two things in the textbook which are pretty useful: first is the 3d spatial visualizations provided and second is the practice questions. One thing to note about the practice questions in the textbook is that the questions for the first two chapters are very elementary and I don't think they can prepare you well enough for the midterms or finals but for the last chapter, I feel that if there are times when you find yourself not understanding what the lecturer is saying, then doing the practice questions will help a lot.

Weightage

Tutorial attendance and participation: 10%

Midterms: 30%

Finals: 60%

The first component is again, free; just present once and attend all tutorials. The coverage of midterms only includes the first two chapters but because I suck at series and sequences, I screwed up the midterms. The best part was I didn't think I'll screw it up that badly. So the median was around 13/30 and I got only 17. Everyone was cursing the paper after the test in Week 8 but truthfully, it was very doable even though I believed the standard of the paper has increased since the last semester this module was offered as the median was around 20/30 back then. As different as the questions may look compared to those in the tutorials, the concepts required were essentially the same (of course). As typical of a mathematics paper, it just depends on whether you can use the appropriate concepts to solve the problems. Anyway, Ji Feng takes a pretty long time to mark; I think our midterm scripts were returned to us only in the tutorial of Week 10.

Finals was cumulative (obviously since there are only 5 chapters) and I thought the focus was on spherical coordinates as bulk of the marks came from that sub-topic. The thing about vectors and multiple integrals is that most people take the formulas for granted and simply neglect the importance of visualization. Being really bad at visualizing in three-dimensional space, I struggled through the last three chapters but I guess it did help make up for all my lost marks on the two finals questions on series and sequences. As long as you can visualize how vector lines or shapes intersect in 3d space, half the battle is already won.

Result: A-

I was expecting at most a B+. I can't say I got an A- because I could do the questions but it was more of the bell curve that saved me. But I think the most important thing is to understand all the concepts; blindly practising questions will not help at all.

ST1131 Introduction to Statistics

Can I just skip this module? The reason is because I never attended even a single lecture or tutorial and I can count with two hands the number of hours I spent on this module in the entire semester which explains my final grade. Ok, there are a few things I can say: given that the content is insanely easy, the bell curve will also be insanely steep especially with ISE majors around. 

Tutorial questions are taken straight from the textbook. By the way, I don't recommend getting the textbook as the notes are just rephrased from there and will be sufficient for revision. Tutorials require the use of Minitab, a software that I've never bothered to use. I mean why use Minitab when you have R right? In fact, I don't find tutorials useful and I gave up after the fourth one.

Weightage

Midterms: 30%

Finals: 70%

Midterms, a 20-MCQ paper, was really stupid with meaningless qualitative questions which were not flattering of Statistics at all. One thing for sure is that this module doesn't give a good indication of what Stats majors will be in for in the following semesters. It just picks a bit from ST2131, a bit from ST2132 and a bit from ST3131 and the bits come together to form one big module. It'll be completely understandable if halfway through, you find yourself questioning where this or that came about because the depth of this module is really... 

The thing about the finals this semester was that the questions seemed a bit open-ended instead of the usual physical science style whereby it has to be this and this only for the answer. There was even an unnecessary question testing on understanding of output from Minitab. 

Result: B+

This result was totally within my expectations as I know how I fared for the finals; feeling sleepy halfway through and doing at 1/10 of my usual pace just says it all. I think even the sloppiness of my review says it all.

ST2137 Computer-Aided Data Analysis

Basically, students will learn 3 softwares: R, SAS and SPSS (you may take the order as a rank of the 'intelligence' of the software beginning with the most intelligent to the least). Most people complain about why we even have to learn SPSS, a software that involves zero coding but clicking instead, when there's R and SAS around. Moreover, the fact that SPSS was totally neglected in the last few topics goes to show something about the software.

This module, for a change, was taken by Lim Chinghway this semester. As good as he is, I don't like the questions he set for the midterms and finals simply because they are not indicative of a supposed programming module. Instead, bulk of the marks came from familiarity with the syntax of the three software through T/F questions. I also skipped the lectures as the thing about programming is that it has to come from your own intuition and understanding. But maybe that is an overstatement given the level of difficulty of this module.

Topics

Introduction to SAS

Introduction to R

Introduction to SPSS

Describing Numerical Data

Robust Statistics for Location and Scale Parameter

Analyzing Categorical Data

One-Sample Tests and Two-Sample Tests

One-Way Analysis of Variance

Regression Analysis
Simulation: An Introduction
Simulation Studies in Statistics
Bootstrap Estimation
Numerical Methods in R

Weightage

Tutorial attendance: 10%

Midterms: 20%

Project: 20%

Finals: 50%

Bonus (IVLE forum participation): 5%

The first component is free. Midterms had 10 T/F questions which served no meaning at all. I mean when you are programming, is there a need to care about nitty gritty details with regards to the syntax? You'll just type the lines and when you realize there's an error, you'll change it and find out later that your code is able to run. I was actually at the 25th percentile with only a score of 35/50 and the median was 41-42 while the 75th percentile was 45. And this just shows how steep the bell curve for this module is. The reason why I screwed up so badly is because first, I lost quite some marks in the T/F questions which was worth 2 marks each and second, I misinterpreted one giveaway SPSS question at the back. Anyway, midterm scripts will be returned during the tutorial two weeks after the midterms but the scores will be uploaded onto IVLE beforehand.

Although the norm is to take this module when you're in Year 2 Semester 1 of your candidature, I strongly recommend to take it only after completing ST2132 and ST3131. It will not only give you an edge over others in terms of the speed at which you understand the content taught here but also, it will allow you to appreciate the content a lot better. Moreover, ST3131 is able to expose you to different methods of regression analysis that are not covered in this module which will allow you to attempt unconventional ways of doing your project like what I have done with my group. Basically, students are not limited in the scope of their project; they can do anything under the sky but you have to prove that you are able to make use of the concepts learnt in class. Students are also free to use any of the three software they wish. Bonus marks will be given if you can come up with something that has not been covered before in class. By the way, credit is given for creativity. The only thing to complain about this project is the limit of 8 pages with reasonable font size but of course, there are ways to get around that using some tricks.

Finals had like 20 T/F questions?! It was absurd yes, 40 marks on that. Well, other than that, finals actually focused quite a lot on theory as the lecturer decided that theory is important to be able to carry out computational analysis which I do agree to a certain extent. But the finals was so easy such that I felt it was impossible to pull up my midterm results. And time was no issue; many people left early.

Result: B+

I did very well for the project and finals which I guessed pulled me back up to a B+ as I was expecting a B- or below. So maybe the bell curve wasn't as bad as I thought. I think if anyone happens to take this module under Lim Chinghway again, know the codes like the back of your hand and I don't actually think that deep understanding of codes is required or at least it won't be tested in either the midterms or finals.

Update on AY2014-15 Semester 1 Module Review

I know the reason for why the number of views on this blog shot up in the past few days is because readers are waiting for my module review to be up. I am already working on it; right now, I'm halfway through but I do not want to sacrifice quality for speed as well. Rest assured it'll be up by this weekend so for now readers, please be patient!

Updated Module Reviews

Now that midterms are over (or at least it was just over for me), some people may be very anxious over their results. But lecturers aren't returning them and you've got no idea how they'll be returning them as well. So I updated all my module reviews to add in this piece of information. I hope it helps a bit.

Anyway, for interested readers, I only know my midterm results for EC4102 and ST1131 as of now. For this semester, I shan't post the scores up at this point in time so look out for my module review during the end of this year.

AY2013-2014 Semester 2 Module Review

Well okay, besides having been occupied for the past month, I did very badly this semester so I needed quite a bit of time to get back up to write this post. Nevertheless, I shall try my best to remain objective so as to benefit the readers of this blog.

CS1010E Programming Methodology

This module was taken by Prof Joxan Jaffar. Apparently, he taught fairly well at the start of the semester, only to deteriorate drastically towards the end. The language taught is C. 

Weightage

Sit-in labs: 50%

Midterms: 10%

Finals: 40% 

This module was basically open-book for every single graded component though I should think that wouldn't help much for a computing module. The main topics covered were control flow, arrays, pointers and structures just like for any other introductory computing module. Sit-in labs were held every odd week (starting from Week 5 onwards) and take-home labs were assigned every other week. If you can do the take-home labs, you might probably consider skipping the lab sessions during the even weeks.

The format of the midterms was as follows: it was a multiple-choice paper comprising of 20 questions; each question has a string of code and you're supposed to interpret it and then choose the option that has the correct output. I actually found it pretty meaningless a paper by the way. But the questions were tricky; sometimes it might just take one semi-colon to make a difference in the solution so exercise extra caution and do not overlook any details. I only got 13/20 which is pretty much below the median I guess. But that is just because I totally neglected one or two topics and there were actually close to 6 questions on those topics so I should think it wouldn't be hard to get above 15. You'll know your midterm results very soon since they'll upload the solutions on the same day itself.

Sit-in labs got progressively harder; there were basically 5 sit-in lab sessions where each subsequent lab was worth 1 more percent than the previous one starting with 8% and ending with 12%. I got A for the first two (but really, anyone can get A for the first one) and B for the remaining ones. That essentially put me in the 50th percentile already. 

Finals was just, bad; pointers, structures everywhere. There were two sections in the finals. Section A was like the midterms just that it was no longer MCQ so that you had to write the output in the blank space provided. There were 15 questions on that. Section B was then testing students on their ability to write codes so as to solve the problems presented in the questions. Personally, I thought some of the questions were quite different from those in the sit-in labs but if you're good at computing, it shouldn't make much of a difference. I basically screwed up both sections and I gave up halfway to the extent that I scribbled some nonsense in Section A. That was how badly I wanted to end this and it doesn't really help that it was my first paper. 

Result: B-

Yes, first B- though it was kinda expected. My advice is to try and get As for all the labs or at least, 4 out of 5. That can secure you at least a B+, I hope. I actually didn't do much practice for this module except  for the take-home labs. In fact, I was quite passive in the sense that I believed practice would only take you so far for a computing module. I am just glad to get over this module which was pretty much useless as C is just obsolete already. If given a choice, I would have loved to take IT1006 but no, CS1010E is a core module for Stats majors.

EC3312 Game Theory and Applications to Economics

This module was taught by Prof Sun Yeneng who was seemingly from the Maths department in FOS. His lectures were so-so as most of the things in the notes were taken from the textbook. I gave up attending them after the first one. Textbook is essential: A Primer in Game Theory by Gibbons.

So there were 4 themes altogether: (1) Static Games of Complete Information, (2) Dynamic Games of Complete Information, (3) Static Games of Incomplete Information and (4) Dynamic Games of Incomplete Information.

Weightage

Tutorial attendance and participation: 5%

Assignments: 10%

Midterms: 35%

Finals: 50%

Basically, attend all tutorials and present once to secure the 5% component, There were 2 assignments, each worth 5%. Assignments were very easy so most people should have no problem securing full marks for them.

The bell curve for midterms was steep; the median was 27/35 and it doesn't help that there are a few PhD students taking this module. So I got only 29 but really, the midterms was actually very easy. The reason why I didn't get above 29 was because there was this particular concept that I didn't clear up before taking the midterms as I started studying only one or two days before the test itself. But the concept itself isn't hard so actually, it shouldn't be a feat to get above 30. Midterms are returned during the next tutorial.

I screwed up the finals especially those questions on Bayesian Nash Equilibrium. Although I could have presented my answers in a more detailed fashion, I don't think it would have helped much as I was pretty weak in that concept itself. The thing about game theory is to really appreciate the big idea. When I was studying for this module, there were many times I had to question myself why this or that has to be done. I just couldn't see the importance in certain things. I mean in reality, most firms aren't going to say, "Ok, so let's formulate our strategies and then work out the Nash equilibrium." It just defeats the purpose of game theory. I took this module actually to train my logic and learn to understand from the perspective of a firm. Unfortunately, I thought there was way too much focus on theoretical concepts so that I didn't actually reap much from this module.

Result: B+

B+ was not shocking given that there were probably only a little over 50 people taking this module and that this module didn't really come as intuitive to me. My advice is that divert more attention to the topics covered after midterms as those will be the main focus of the finals. Well honestly (and I'm not saying this cos' I didn't do well), this module is close to useless unless you want to go on to higher-level modules or do your thesis on something related to game theory. I mean the emphasis on the theories of Nash Equilibrium was just way too much such that I don't see the realism in this module.

EC3333 Financial Economics I

This module was taught by Prof Lu Jingfeng whose English may be a bit hard to comprehend (I seldom comment on such things but if I have to say it, that just means something). But then again, if you don't go for lectures... 

And so this was one module I really disliked and for the first time, I actually regretted taking a module. I thought nothing could get worse than micro in terms of the level of interest but this was just many times worse than micro. Aside from the fact that everything was being thrown at you without any avenues to enhance your understanding (I tried to look for a book that derives all the theories and formulas but to no avail, neither was asking the Prof a solution as well), this module was way too technical for my liking. So it's just formulas and graphs and formulas again.

Topics covered are Optimal Risky Portfolios, CAPM, APT, Bonds and Options. I personally think the textbook was bad (no derivations) but still necessary for this module since the notes are mainly slides created out of the content in the textbook: Investments and Portfolio Management by Bodie, Kane and Marcus, 9th Edition. Note: Investments by Bodie, Kane and Marcus, 9th Edition is almost identical and can be used as a substitute.

Weightage
Tutorial Attendance and Participation: 15%
Assignments: 15%
Midterms: 30%
Finals: 40%

The first component is supposedly easy to get, just attend all tutorials and participate three or four times in class. Similarly, the second component is supposedly easy to get as well but unfortunately, I did not get full marks for the last two assignments. Basically, how it works is that each student gets allocated 3 assignments at random so some may get the ones in the earlier weeks and some may get a mixture of those in the earlier and later weeks. Well, the impression it gives is that it might be somewhat unfair since those who got allocated the tutorials covered in the earlier weeks (especially before the midterms) have it easier. But really, I think the assignments are all easy and given enough understanding, one should be able to score full marks for all of them.

The midterms was disastrous for me. I got a mere 21/30 when the average was probably around 25.5 to 26. Reason: This exact same question from the practice midterms came out and I screwed it up. Yes I did not practise the midterms but aside from that, I think even if I did not, I should have been more careful and have a deeper understanding of the concepts involved. Then there was another question in which I got the correct answer at first but having been too paranoid, I decided to act smart and write something else so I got that wrong too. In fact, there was only one 'differentiator' question which oh, I happened to answer it wrongly as well. That, I can only blame myself for not understanding the earlier chapters thoroughly. In fact, I think the midterms is really doable and it wouldn't have been hard to get at least 26 or something along that line. Anyway, midterm scores will be uploaded onto IVLE once grading has been done.

Finals. Finals was apparently easy since I got a B and I thought I did pretty well. So it's either I underestimated the cohort (doesn't help that there are a few DDP students taking this module) or I overestimated myself. I think it's a mixture of both. Proofs can be easily found in the textbook and yes, contrary to what I thought, many people actually read them. Other than that, it's all just simple calculations and manipulation for one question.

Result: B

ST2132 Mathematical Statistics

Well, the first thing I must say is that as intimidating as Prof Lim Chinghway looks, he's one heck of a good lecturer. He's patient, willing to help, explains concepts really clearly and would even repeat if the class did not catch it. Possibly almost everything you would want to see in your lecturer.

The fact is that this module is very easy compared to ST2131. Like I said, Prof Lim toned it down a lot so that it transformed from a killer module to a CAP-puller for most people I guess.

The big topics covered included Simple Random Sampling, Parameter Estimation (MOM and MLE), Fisher Information, Efficiency, Sufficiency, Hypothesis Testing, Generalized Likelihood Ratio Test and the Comparison of Two Samples. Textbook isn't necessary at all since the notes are sufficient and tutorial questions are from there as well but you could still get it if you want: Mathematical Statistics and Data Analysis by John Rice, 3rd Edition.

Weightage
Tutorial Attendance: 5%
Tutorial Participation: 5%
Assignments: 20%
Midterms: 20% (graded on completeness and also, correctness from Week 2 or 3 onwards cos' they found a grader)
Finals: 50%
Bonus: 5% (for participation either in class or on IVLE Forum)

The first 3 components are free marks so there's no need to talk about them (because you are actually allowed to make changes to your tutorial answers when your tutorial mates are presenting their answers).

I screwed up midterms as usual, got only 24/40. Average was 22 or something. The questions were easy but one of them was pretty unprecedented. But on overall, I must say the Semester 2 paper was harder than Semester 1 paper (and much less people take ST2132 in Semester 2). Even so, it was still doable. Highest was 38/40 by the way. So the S.D. is pretty high. The midterm score was uploaded onto gradebook before the scripts were returned to students during tutorial.

Finals was easy as well. Know your concepts well and trust me on this, copy down all the probability mass or density functions onto your cheatsheet. You'll need it during the exam. With that, you can easily get a decent grade provided you know what you are doing.

Result: A-
Probably got saved by the finals.

ST3131 Regression Analysis

Personally, this is one of the hardest Stats modules I have taken. The level of understanding involved in this module on top of the derivations is not trivial. Oh plus the bell curve is very steep with lots of Maths majors screwing it up. From what I heard, this module used to be on the same level as ST1131. However, since Prof Anthony Kuk took over, it became quite difficult a module.

Coupled with procrastination, I was always lagging behind lectures (I don't go for lectures partly cos it's 8am and partly cos going for lectures isn't gonna make much of a difference). I never attended tutorials as well since the tutor is atrocious as everyone has made him out to be.

Topics covered ranged from 1-factor ANOVA, 2-factor ANOVA to simple, multiple, subset regression, residuals, outliers and the combination of ANOVA with regression. There was no compulsory textbook for this module. All were just references but the main one was Introduction to Regression Analysis by Montgomery, Peck and Vining, 5th Edition.

Weightage
Assignments: 20% (2 assignments worth 10% each)
Midterms: 20%
Finals: 60%

Most people got full marks for assignments which mainly made use of R (I did not though). R isn't tested in finals by the way. Midterms was just plugging in formula. Well, the thing about midterms was that you didn't have to understand what you are doing, you just have to know what to use. Average was around 30/40. The midterm score was uploaded onto gradebook before the scripts were returned to students during lecture.

Finals was the hard one for me or probably for many people. So nothing in the notes appeared and they were all out-of-context questions. This just boils down to how well you understand the concepts and yes, because I didn't, I screwed the finals up badly. But the finals was really typical of an open-book exam where you had to think on the spot and manipulate some stuff. Time wasn't a constraint though.

Result: B
No doubt finals is the determining factor since I got full marks for midterms but at the same time, no doubt that this module is important. My advice is be consistent, clarify doubts immediately, don't ever snowball anything.

AY2013-2014 Semester 1 Module Review

EC3101 Microeconomic Analysis II

This module was taken by Prof Mcgee. I personally think the textbook is useless, not to mention its exorbitant price. The lecture notes (which are actually ppt slides from the publisher) are sufficient. But for anyone who's interested, the textbook used is Intermediate Microeconomics by Hal Varian, 8th Edition.

Topics covered before Week 7

Review of topics covered in EC2101 like budget line, indifference curve etc.

Intertemporal Choice

Uncertainty (covered in EC2101)

Exchange

Externalities

Topics covered after Week 7

Game Theory

Game Applications

Oligopoly

Asymmetric Information

Weightage

End-of-tutorial quizzes: 10% (best 8 scores will be counted)

Homework: 20% (one before and one after midterms)

Midterms: 30%

Finals: 40%

The midterms tested on all the topics covered before Week 7. The median for midterms was 54/100. I scored only 63 as I made countless careless mistakes in the midterms. On top of that, having only 1 hour 45 minutes for 7 questions was pretty insane; most people couldn't finish. In addition, Prof Mcgee likes to use algebra in his questions so it is important to exercise extra caution when writing those complicated expressions. Anyway, you have to go to the general office to collect your midterms.

Finals wasn't cumulative and only topics taught from Week 7 onwards were tested. Having said that, the finals will obviously be more difficult but there is less of a problem in terms of time constraint.

Result: B

For this semester, the emphasis in the finals was on asymmetric information which happened to be my weakest topic, resulting in a mediocre overall grade. On the other hand, the questions on game theory and game applications were rather simple.

The important thing for this module isn't practice but understanding of concepts.

EC3102 Macroeconomic Analysis II

This module was taken by Prof Ho Kong Weng. There were approximately 15 chapters covered in total including IS-LM, AD-AS for closed and open economy. I strongly recommend getting the textbook for this module even though many people commented that the notes were sufficient and that there wasn't time to refer to the textbook anyway. But I self-studied this module all the way so I needed the textbook. Even so, I think the textbook is much better than the notes as the notes is simply a summarized version of the textbook. The textbook used is Macroeconomics by Blanchard and Johnson, 6th Edition.

Weightage

Tutorial attendance: 10%

Tutorial participation: 5%

Midterms: 35%

Finals: 50% (open-book)

Midterms consisted of 4 questions to be done within one hour. Many complained that the time was insufficient. As typical of Prof Ho, he likes to twist the expressions we have learnt in class to test whether you fully understand the concepts. Also, Prof Ho only releases z-score for midterms, 0 being the mean while positive scores mean you are above the average and vice versa. I got 2.0 for the midterms as I screwed up one question on lagrange multiplier. (The question wasn't difficult but it was just because I had no idea how to do lagrange multiplier at all since I took MA1102R in place of EC2104 and instead of self-studying multivariate calculus when I could last summer, I procrastinated.) Typical of Prof Ho, midterm z-scores were uploaded on IVLE.

Finals on the other hand did not seem to test you on your concepts but rather, on your derivation abilities. In fact, I think even if I had not studied, I would still be able to do the paper.

Result: A

I did not do very well for the finals as well because there were many things I did not explain properly due to the lack of time. That was probably the main reason why I ended up with an A.

EC3314 Mathematical Economics

This module was taken by Prof Goenka. There was a total of only 8 or 9 chapters covered. This module is one of those few Level-3000 electives offered in only one semester. In fact, very few FASS students will take this module and majority of the students are from FOS or FOE. On top of that, the total number of people enrolled in this class is only 44 which shows how steep the bell curve can get. Plus, only the last topic covered was new for most FOS students. Lectures aren't really very useful (I skipped lectures from Week 8 onwards though I do watch webcasts for the last two lectures).

Nevertheless, I took this module as I found the content covered to be quite useful and it is the only level 3000 elective that is really mathematical in nature.

Topics covered include

Review of Linear Algebra

Static Optimization

Nonlinear Programming

Dynamic Optimization

Weightage

Tutorial attendance and participation: 10%

Homework: 20% (one before and one after midterms)

Midterms: 30%

Finals: 40%

The mean for midterms was 35/45 and I scored 40. The 5 marks lost was purely due to carelessness. But the midterms was really easy; there wasn't any proofs or even derivation. All the questions tested on was the ability to apply. I think even the first homework was more difficult than the midterms. Apparently, the midterms had to be collected from the general office but I had no knowledge of that until probably Week 10 or 11 (because I did not attend his lectures and he did not make an announcement on IVLE).

The finals was of course a lot more difficult. In order to score, you had to display a certain level of understanding especially for concepts like upper and lower hemicontinuity, correspondence and the maximum theorem but the Prof did not explain these clearly. I actually thought I screwed up the finals really badly as I could not get the full answer for the dynamic programming question and that my understanding of the above-mentioned concepts was still very shaky. The only question I was really confident of securing full marks was the one on nonlinear programming.

Result: A-

Understand the concepts covered during lectures and tutorials. Practise if possible. Oh by the way, the textbook is Further Mathematics for Economic Analysis by Sydsaeter, Hammond, Seierstad and Strom, 2nd Edition.

EC3341 International Economics I

This module was taken by Dr Lu Yi. He is a very helpful lecturer and will answer your queries promptly. A total of approximately 9 chapters was covered. A lot more emphasis was given to the micro topics of trade. Many had said that Dr Lu's lectures were good as there was additional information given and he would take extra effort to go through the more difficult concepts. However, I did not attend the lectures and self-studied this module based on the notes and textbook which I do agree caused me to lose out a bit on some crucial information as well as assignment marks. But the textbook was probably not really necessary though I still recommend to get it: International Economics Theory and Policy by Krugman, Obstfeld and Melitz, 9th Edition.

Topics covered include

Ricardian Model

Specific-factors Model

Heckscher-Ohlin Model

Standard Trade Model

Monopolistic Competition

Money, Interest Rates and Exchange Rates

Price Levels and Exchange Rates in the Long Run

Weightage

Tutorial participation: 10% (but actually I think you can get that full 10% by just attending tutorials)

Weekly assignments: 30% (10 assignments in total)

Group project: 10%

Finals: 50%

There were no tutorials for this module. Basically, students were expected to finish an assignment every week and during the tutorial, the tutor would go through the solutions for the assignment that had been submitted.

Group project was simply comments on two papers that Dr Lu has chosen. There wasn't any word limit.

For finals, there was one macro question while the other three questions were micro. Past-year papers may help in scoring for finals but understanding the concepts well is a lot more crucial.

Result: A

I gave up quite some marks in the assignments plus I think I did not do that well in the finals hence resulting in only an A. Even so, I should think that the bell curve for this module was not really that steep though there were less than 100 people taking this module but many of them were exchange students.

PH1102E Introduction to Philosophy

This module is taken by Prof Pelczar. He is a really enthusiastic prof but maybe philo is just not my thing, so I did not attend his lectures. Readings for this module were actually not very long but even for the longer ones, you would just know which parts to skip based on experience.

Themes covered

Free Will

Moral Philosophy

Philosophy of Religion

Philosophy of Mind

Metaphysics

Weightage

Tutorial attendance and participation: 10%

Weekly summaries: 50%

Finals: 40%

For the weekly summaries, students will be expected to summarize the assigned reading. However, it is important to keep in mind what the question is asking exactly. My advice is that for most summaries, do not attempt to source for information outside of the reading unless otherwise stated. There were a few times at the start that I did this in the hope of getting higher score only to end up with a mediocre score. The summaries are bell-curved. I scored only 6/10 for most summaries and 8/10 for a few. There is also one MCQ Quiz (which are PYP questions) to be submitted during Week 7 in place of the summary.

Finals was a 20 MCQ paper. I could check the paper 4 or 5 times even before the first hour ended. Most people will leave after the first hour. However, the questions tend to be tricky so study your lecture notes (not readings or ppt slides) well. That is all you need for the finals. As the prof said himself, only a handful of people out of a cohort size of almost 300 can score 18 and above for the finals which tells you how gentle the bell curve for finals is.

Result: A-

Despite scoring only slightly above average for the summaries, I could still pull up my overall grade to an A-. What I did was to study the lecture notes in detail and with consistency as well as practise the PYP.