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Alison Choi

May 7th, 2020

Survival guide of a marketing student with no analytical background

2 comments | 1 shares

Estimated reading time: 3 minutes

Alison Choi

May 7th, 2020

Survival guide of a marketing student with no analytical background

2 comments | 1 shares

Estimated reading time: 3 minutes

Student Ambassador Alison Choi reflects on her experience at LSE. With no analytical background read how she overcame doubts and her tips for students wanting to grow their data analysis skills.

MSc Marting students at LSE

Pictured with my lovely friends Ayush, Shivani, Tammy on the last day of Michaelmas term

 

Overcoming the quantitative portion of my degree

Marketing today is all about big data. As a humanities undergraduate student, I possessed limited numerical abilities. A big part of my reasoning for applying to the MSc in Marketing at LSE was grounded in my endeavour to dive into the wondrous world of data analytics and hopefully become good at it in the process.

While I originally thought that I was ready for the quantitative challenge of the degree, my initial bravado started to falter when statistical formulae and concepts were introduced. Despite feeling like I understood everything during lectures, the moment I got home everything would become a blur.

My imposter syndrome kicked into high gear as I began questioning my capability to excel in the degree.

Despite feeling like I understood everything during lectures, the moment I got home everything would become a blur.

Tick tock, time to rock

All the self-doubt and uncertainty halted when group work rolled in after reading week. In order to not let my group mates down, it was imperative that I stopped wallowing and got to work.

I managed to build a solid foundation of data analytics by the end of Michaelmas term and can now navigate R programming language to conduct basic analyses by myself – something I would have never guessed I could do merely six months ago.

Reflecting back, here are some tips and tricks that really helped me:

 

1.Prep beforehand

As a novice in statistics, I found it difficult to follow through in class with no prior understanding of the material. To combat this issue, I would go through the syllabus before class and do some light research to acquaint myself with unfamiliar numerical concepts. As an avid visual learner, YouTube was my best friend to accessing digestible educational content.

2.Book office hours in advance

I remember feeling so relieved when I finally comprehended the numerical concepts – but little did I know that actually applying them to real data analysis is a whole other challenge. This is when guidance from professors is most vital and useful. But as deadlines crept in, my fellow classmates also needed assistance. As such, booking office hours in advance was crucial. Having my professor answer my queries and check the logic of my analyses made me feel a lot more grounded in my first data analysis attempt.

3.Lean on your teammates

Teamwork makes the dream work! My teammates were my go-to support when in doubt. LSE is a gathering place of students with many unique talents and I was able to capitalize on this to flesh out ideas and work through solutions with others who are more adept at data analysis. I truly give many thanks to my groupmates for their generous help in getting me through struggles and frustration.

LSE is a gathering place of students with many unique talents

Last day of lent term with my friends Shivani, Priscilla, Claire, and Tammy

 

With a good support network and a bit of discipline, I overcame my fears of data analytics. While I still have a lot more ground to cover, I am so much more comfortable with numbers now. I look forward to getting better and becoming an all-rounded marketeer with rich creativity and quantitative ability.

While I still have a lot more ground to cover, I am so much more comfortable with numbers now.


Learn more about our MSc Marketing programme

About the author

Alison Choi

MSc Marketing Student 2019/20

Posted In: In the classroom | The Student Lens

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