ST3131: Regression Analysis
Lecturer: Wang Junshan
This is a core module for Statistics students. You should expect to learn about Regression and how to fit to your data to a suitable model.
The lecturer is a first-timer, so her teaching is lacking and she also uses last semester's notes. Thankfully, she understands her own shortcomings and encourages us to give her feedback, she also adds on her own comments to the lecture notes. I kind of pity her because she received feedback that students would prefer webcast, but after she started the webcast, students started skipping lectures(me included oops) and the LT became super empty. It also does not help that the lecture is at 8am, the ungodly timing.
Workload is easily manageable, there are weekly tutorials which are kind of useless. The only work is the group project, which requires you to form your own groups then find a dataset online and perform regression analysis on it. I knew that there was a project beforehand but the lecturer only gave it out in Week 9, and we had exactly 4 weeks to complete it..... I was lucky to be grouped with this genius guy who offered to do all the coding for us :) Midterm and finals were totally manageable too, cheatsheets allowed, the questions usually show you the output from R/SAS and then you have to calculate certain stuff based on the output. This also explains why I don't remember doing any coding for this module hehe. It is totally possible to not attend tutorials and still get a decent score.
This is a core module for Statistics students. You should expect to learn about Regression and how to fit to your data to a suitable model.
The lecturer is a first-timer, so her teaching is lacking and she also uses last semester's notes. Thankfully, she understands her own shortcomings and encourages us to give her feedback, she also adds on her own comments to the lecture notes. I kind of pity her because she received feedback that students would prefer webcast, but after she started the webcast, students started skipping lectures(me included oops) and the LT became super empty. It also does not help that the lecture is at 8am, the ungodly timing.
Workload is easily manageable, there are weekly tutorials which are kind of useless. The only work is the group project, which requires you to form your own groups then find a dataset online and perform regression analysis on it. I knew that there was a project beforehand but the lecturer only gave it out in Week 9, and we had exactly 4 weeks to complete it..... I was lucky to be grouped with this genius guy who offered to do all the coding for us :) Midterm and finals were totally manageable too, cheatsheets allowed, the questions usually show you the output from R/SAS and then you have to calculate certain stuff based on the output. This also explains why I don't remember doing any coding for this module hehe. It is totally possible to not attend tutorials and still get a decent score.
ST3239: Survey Methodology
Lecturer: Kuk Yung Cheung, Anthony
WHY WHY WHY did I even use up 1000 of my bidding points for this stupid module? I thought that I would be learning how to conduct surveys and analyse the results (ok I actually did learn those stuff) but I felt like I gained nothing from this module.
I blame the lecturer. First, his notes are bad. I don't understand the explanations, and there were a whole bunch of useless stuff. Second, the teaching is boring. He keeps jumping here and there and I lose track of what he is saying. Usually I'm more excited for his tutorials because I actually learn more stuff by just copying the damn answers to the tutorial questions. Unfortunately, I was still forced to attend lectures since there was no webcast.
There are 2 assignments given out, which consist of around 2 questions each. For me, I just kept flipping through the notes until I think I found the correct formula, because that is what this module is about: using the correct formula. Midterm and finals were ok, but for me I forgot to copy a formula into my cheatsheet during the midterm and it was tested. Oh well, just blame my luck. The papers also had a question or two taken from the lecture notes/tutorials.
ST3247: Simulation
Lecturer: Vik Gopal
This module is hard but actually fun? Basically we learn how to generate distributions, Poisson process, how to do discrete event simulation, Monte Carlo integration, variance reduction, etc. Coding for this module is done using R Studio, so do not forget your stuff from ST2137, as well as some basic stuff like writing loops from CS1010S.
The lecturer rocks! His notes are straightforward, and he explains the stuff really really well. I always have a lot of stuff to copy during his lectures because his explanations are really good and I just had to write down all the things he says. My friends complained that he spoke too fast and they had to watch the webcasts sometimes, but personally I found the speed ok. I guess maybe he did go really fast though, he finished the syllabus early and kept dismissing us early during the last few weeks (yay for avoiding squeezing up the shuttle bus to the mrt!)
Workload might be a little high. There are 4 assignments, and all the assignments have a coding and a written portion. I spend quite a lot of time for each assignment, but luckily I still remember some programming skills so I could manage the questions. Midterm and finals were ok, the worst part was no cheatsheets allowed! I wanted to pull my hair out trying to remember all the various algorithms for generating the distributions. I have to admit that the questions were actually well set, with various difficulties that test your understanding of the various concepts. If I find that this lecturer is teaching other stats modules, I will definitely go take them.
DSC1007X: Business Analytics - Models & Decisions
Lecturer: Tung Yi-Liang
Ok, I took this module for an easy life. The first half of this module is basically statistics (probability and probability distributions) while the second half is about optimization. DO expect a lot of math, stats, econs, engineering students taking this module. If you do not have the relevant background, be prepared to do a lot of catching up.
The lecturer was ok I guess. I think he used the same slides as the DSC1007 module? Not sure about that. I cannot really give comments about the teaching since I have already learned most of the syllabus before, so regardless of the standard of teaching, I can still understand the module. The lecturer is really friendly though.
Workload is manageable. The work assigned are all easy if you have the relevant background. There are weekly group assignments which are easy, there is also a group project(same group) about doing simulation on Microsoft Excel, and there are individual quizzes fortnightly during the tutorial sessions. Despite this super easy module, I had a lot of trouble due to my lousy groupmates. The groups were randomly assigned and I got stuck with a bunch of... yeah you get it. Do you know how it feels to be able to do the assignment questions every week but you cannot submit your answers because you are forced to "discuss" with your groupmates who don't respond to your whatsapp messages? UGH, ok no more talking about the group, they don't deserve such a big space on my blog. The finals were totally easy, cheatsheet allowed, question topics already announced beforehand and we took the same exam paper as the DSC1007 people (but different bell curve!). Apparently, we scored better than the biz peeps from DSC1007 hahaha :P
LSM1301: General Biology
Lecturers: Loh Chiang Shiong, Wu Jinlu
This module is a popular module for its easy and slack syllabus. Only people without H2 Biology are allowed to take this module. Topics covered are similar to O-level and A-level Biology.
There are 2 lecturers for this module. The lecturer for the first half was not bad, he cracked a lot of jokes and the lectures were enjoyable. The lecturer for the second half was from China, so his lectures were harder to understand because of his pronunciation. But overall the lectures were fun, no webcasts but it was beneficial to attend the lectures as you do get to learn a lot of useful stuff. My interest towards Biology increased after taking this module, but not enough to take the Life Sciences stuff (oops hehe sorry).
Workload is super light. Only 4 assignments to be submitted online, just google for the answers and fill in the Word document. There was also a lab session where we get to explore stuff like using a microscope as well as the gel electrophoresis. Finals were all MCQs and open-book, so expect a steep bell curve. The lecture notes are insufficient to score well, so try to borrow your friend's textbook or something.
WHY WHY WHY did I even use up 1000 of my bidding points for this stupid module? I thought that I would be learning how to conduct surveys and analyse the results (ok I actually did learn those stuff) but I felt like I gained nothing from this module.
I blame the lecturer. First, his notes are bad. I don't understand the explanations, and there were a whole bunch of useless stuff. Second, the teaching is boring. He keeps jumping here and there and I lose track of what he is saying. Usually I'm more excited for his tutorials because I actually learn more stuff by just copying the damn answers to the tutorial questions. Unfortunately, I was still forced to attend lectures since there was no webcast.
There are 2 assignments given out, which consist of around 2 questions each. For me, I just kept flipping through the notes until I think I found the correct formula, because that is what this module is about: using the correct formula. Midterm and finals were ok, but for me I forgot to copy a formula into my cheatsheet during the midterm and it was tested. Oh well, just blame my luck. The papers also had a question or two taken from the lecture notes/tutorials.
ST3247: Simulation
Lecturer: Vik Gopal
This module is hard but actually fun? Basically we learn how to generate distributions, Poisson process, how to do discrete event simulation, Monte Carlo integration, variance reduction, etc. Coding for this module is done using R Studio, so do not forget your stuff from ST2137, as well as some basic stuff like writing loops from CS1010S.
The lecturer rocks! His notes are straightforward, and he explains the stuff really really well. I always have a lot of stuff to copy during his lectures because his explanations are really good and I just had to write down all the things he says. My friends complained that he spoke too fast and they had to watch the webcasts sometimes, but personally I found the speed ok. I guess maybe he did go really fast though, he finished the syllabus early and kept dismissing us early during the last few weeks (yay for avoiding squeezing up the shuttle bus to the mrt!)
Workload might be a little high. There are 4 assignments, and all the assignments have a coding and a written portion. I spend quite a lot of time for each assignment, but luckily I still remember some programming skills so I could manage the questions. Midterm and finals were ok, the worst part was no cheatsheets allowed! I wanted to pull my hair out trying to remember all the various algorithms for generating the distributions. I have to admit that the questions were actually well set, with various difficulties that test your understanding of the various concepts. If I find that this lecturer is teaching other stats modules, I will definitely go take them.
DSC1007X: Business Analytics - Models & Decisions
Lecturer: Tung Yi-Liang
Ok, I took this module for an easy life. The first half of this module is basically statistics (probability and probability distributions) while the second half is about optimization. DO expect a lot of math, stats, econs, engineering students taking this module. If you do not have the relevant background, be prepared to do a lot of catching up.
The lecturer was ok I guess. I think he used the same slides as the DSC1007 module? Not sure about that. I cannot really give comments about the teaching since I have already learned most of the syllabus before, so regardless of the standard of teaching, I can still understand the module. The lecturer is really friendly though.
Workload is manageable. The work assigned are all easy if you have the relevant background. There are weekly group assignments which are easy, there is also a group project(same group) about doing simulation on Microsoft Excel, and there are individual quizzes fortnightly during the tutorial sessions. Despite this super easy module, I had a lot of trouble due to my lousy groupmates. The groups were randomly assigned and I got stuck with a bunch of... yeah you get it. Do you know how it feels to be able to do the assignment questions every week but you cannot submit your answers because you are forced to "discuss" with your groupmates who don't respond to your whatsapp messages? UGH, ok no more talking about the group, they don't deserve such a big space on my blog. The finals were totally easy, cheatsheet allowed, question topics already announced beforehand and we took the same exam paper as the DSC1007 people (but different bell curve!). Apparently, we scored better than the biz peeps from DSC1007 hahaha :P
LSM1301: General Biology
Lecturers: Loh Chiang Shiong, Wu Jinlu
This module is a popular module for its easy and slack syllabus. Only people without H2 Biology are allowed to take this module. Topics covered are similar to O-level and A-level Biology.
There are 2 lecturers for this module. The lecturer for the first half was not bad, he cracked a lot of jokes and the lectures were enjoyable. The lecturer for the second half was from China, so his lectures were harder to understand because of his pronunciation. But overall the lectures were fun, no webcasts but it was beneficial to attend the lectures as you do get to learn a lot of useful stuff. My interest towards Biology increased after taking this module, but not enough to take the Life Sciences stuff (oops hehe sorry).
Workload is super light. Only 4 assignments to be submitted online, just google for the answers and fill in the Word document. There was also a lab session where we get to explore stuff like using a microscope as well as the gel electrophoresis. Finals were all MCQs and open-book, so expect a steep bell curve. The lecture notes are insufficient to score well, so try to borrow your friend's textbook or something.
