Up to this date, I vividly recall my first (business) Statistics-course at HKUST (Hong Kong University of Science and Technology). It was gruelsome for a number of reasons:
- I simply did not understand certain concepts the teacher was conveying (or trying to). Luckily my classmates and I could rely on Khan-academy, but at times I still wasn’t sure on how I was doing in this course.
- I did not see the relevance of many of the concepts. How did they even relate to my field of study? When would I be using them?
- The only motivation to study were the two midterm exams and the final exam. Those exams were open-notes (one sheet of A4-paper) and open-book, respectively, so I felt a (probably wrong) sense of security.
After the final exam in December 2011 I was determined to not deal with Statistics again (at least in academics), and I even sold my book to a junior-student.
It wasn’t before I came to National Chengchi University (NCCU) as an exchange student that I took another, second course in Statistics (adequately named Statistics II). I really loved that course. It’s been a great ride, for a couple of reasons:
- This time around, the teacher encouraged us to dig deep into the assumptions of various statistical tests and distributions, and challenge them.
- This time around, I actively used Excel to solve assignments, which in and of itself is a great learning experience.
- The hard and less-common concepts make the more-common concepts seem easier.
I really wouldn’t want to miss taking this course, and I am grateful for this opportunity to expand my background in Statistics. For one, because businesses rely on an ever increasing number of data. Let’s face it, most of us will have to deal with data in our professional lives. It has been said that data-scientists are the “sexiest job” of the 21st century. I guess you don’t need to be sexy yourself, but who doesn’t want to be able to talk to and understand sexy people? And finally, statistics can help us make better decisions. When businesses generate incredibly vast amounts of data every day, isn’t it somewhat fair to assume that the answer is already contained? Or at least a hint or two? If it’s possible to effectively and efficiently dig through these amounts of data, come up with results, and make decisions based on what you’ve found, then I firmly believe that our decisions will be better in a large number of instances.
It’s time for more Statistics at university! Let’s enroll!