Wednesday, 27 May 2015

The End of a Chapter

How time flies.. 4 years had zoomed past, and my journey as a student has officially ended. When I was in JC, I have always had a knack for Statistics despite my distaste for Mathematics. Upon my JC graduation, I wanted a uni course which interest me, leverages on my strengths, and promise a certain level of career prospect. Statistics naturally fulfilled the first 2 criteria, but I was uncertain about the career prospect for a statistician or a statistics graduates, especially in Singapore's context. I did some research online then, but the relevant information were scarce. In the end, I took a leap of faith and accepted NUS Science with a very murky idea of the potential career opportunities. On hindsight, I am glad that I have chosen this course. 

The Programme
The statistics course in NUS is not going to be easy. Getting a First Class Hons will not be a walk in the park. With a significant number of foreigners who are brainy and hardworking, the competition is steep.

Comparing with economics modules, the workload of statistics mods tends to be heavier and requires more effort to understand. It is perfectly normal to leave a statistics lecture utterly confused, especially if  you did not skimmed through the reading materials before the lecture.  

Do a Double Major. 
For those who have the capacity to do more, consider a double major. 

The Statistics curriculum consists of one of the highest number of unrestricted electives (36MCs) compared to many other majors. This gives statistics students considerable flexibly to take on a second major without being heavily overloaded. For example, with careful planning, one can fit a second major in Economics into the programme requirement without additional coursework.

A double major do matters to the employers, and will enhance your employability. Apart from the intangibles like demonstrating your diverse interest and knowledge, your willingness and ability to do more than the minimum, certain combinations of majors are highly valued by employers. Combinations such as Statistics + Economics or Statistics + Computing are highly complementary, and for the latter, I foresee a rising demand for such graduates. Needless to say, a second major will also broaden your career options. Personally, a double major did opened up more opportunities for me, and I would not have secured my relatively-well-paying job offer without my second major. 

Career Paths
Majority of the statistics grads should not face much difficulties securing a job, especially for students who are graduating with honors. Many of my course mates managed to secure job offer(s) before the final exams. Some of the possible career paths available to statistics grads include:

Healthcare (Clinical Analytics) 
Biostatisticians with the various healthcare/research facilities and healthcare authorities 
Statisticians in the private and public sectors. 
Banking (risk, analytics, ops and tech) 
Data Analytics
Market Research

However, some of these jobs have high barrier of entry, and so I would advise you to start preparing for your career as early as possible. Join networking session to find out what are the entry requirements for the job (pro. qualifications/exams, relevant internships, etc.). Get relevant experience through internships. Attend some career workshop conducted by NUS career center.

Let me end this section with a quote from Google's Chief Economist, Hal Varian, on statistics and data.

“I keep saying the sexy job in the next ten years will be statisticians. People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s? The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it.” – Hal Varian, Google’s chief economist

Modules Ranking
Finally, here's my personal ranking for the modules I have taken over the past 4 years. They reflect my interest, preference, strengths, and weaknesses. Therefore, my experience with these modules may be wholly different from yours. 

Most interesting mods
1. GEK1508 Einstein's Universe and Quantum Weirdness by Prof Phil Chan
2. EC3312 Game theory and Application to economy by Luo Xiao
3. EC3333 Financial Economics I by Lim Boon Tiong

For those who are intrigued by the movie Interstellar (2014), I highly recommend GEK1508. The module explores the intricacies of Relativity, Quantum Mechanics and strings. Prof Phil Chan is also an extremely passionate lecturer who makes the lectures an enjoyable experience. Easily the best module I have taken in NUS.  

Most Difficult ST mods
1. MA2108 Mathematical Analysis I by A/P Lee Soo Teck
2. ST3236 Stochastic Processes I by Sun RongFeng
3. ST3246 Statistical Models for Actuarial Science by A/P Lim Tiong Wee

Most Useful mods
1. ST2137 Computer Aided Data Analysis by Dr. David Chew
2. ST4231 Computer Intensive Statistical Methods by Alexandre Hoang THIERY
3. ST3239 Survey Methodology  by Dr. Chua Tin Chiu

Apart from the Most Useless modules listed below, many of the ST/MA lvl1000-2000 mods are useful for building up our foundation in understanding and applying statistics. The top 3 listed here are special mentions which I think are very useful in both industrial and academia. 

Mose Useless mods
1. MA2108 Mathematical Analysis I by A/P Lee Soo Teck
2.  ST3236 Stochastic Processes I by Sun RongFeng

I don't recall much from these two modules. Basically, they are just learn-and-dump mods as I have not applied anything from these two modules for any of my higher level modules.  

Most Difficult EC mods
1. EC3312 Game theory and Application to economy by Luo Xiao
2. EC3333 Financial Economics I by Lim Boon Tiong

Easiest EC mods
1. EC2101 Microeconomic Analysis I by Zhang Yang
2. EC3101 Microeconomic Analysis II by SNG Tuan Hwee
3. EC3361 Labor Economics I by Peter James McGee

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