R Open Lab Reflections

Sharing is always good!

I am really happy to get a great opportunity to work for Digital Center in my last semester at Columbia as a R Open Lab Intern in Digital Center Internship Program.R is really a powerful tool for statistic and data science nowadays which I love most. Holding weekly R Open Lab and daily consulting really give me good experience to teach and share my understand of data and R programming. During this process, I also refresh my own idea by interacting with people from different academic background.

Teaching and sharing are quite different from just telling the knowledge. When I was deciding where to start and how to explain every idea clearly, I was thrown back to the moment when I was new to R, such as “what foundation is important but tricky?”, “what mistake will we make if we are confused with some concept?”. Most importantly, this is always the idea that guide me how to teach in the whole semester. Nowadays there are tons of material people can find online to get them familiar with a programming language, but I think our Open Lab is great place for (1)getting idea of where to start; (2)improving understand of R.

In R Open Lab, I followed the roadmap of basic knowledge of variable type, data structures, functions and environment, data manipulation, exploratory data analysis/ visualization, apply family, text analysis, R Shiny, which starting with the fundamentals and going to more applied knowledge.

I always went forward and backward when we met fundamentals during teaching something new and gave enough exercises after each new concept, which can not only remind the attendee the fundamental but also satisfy them when they know that they really learnt the knowledge. Discussions and questions were always encouraged during lab, which means that every attendee engaged in the lab and thought by themselves.

In the consulting part,  I have to say it is really worthwhile to take time listening to people’s question, clarifying it and solving together. During this semester, I worked on different problems from coding in R, statistical modeling and data analysis. I realized that it is often the case that people come with error but have no idea about what their question really is, I always talk with them, dig into their problems and try to find out the real question. It is a skill for problem solving. I also improved my own knowledge like building boosting models and writing SQL in R to simplify data manipulation.

I recommend this internship program. Sharing what we have and learning from people are what we need to do all the time.


Hanying Ji
M.A. Statistics (2018)

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