ESS 2019
Participating in the Quantitative Text Analysis course of the Essex Summer School in Social Science Data Analysis was truly a memorable and eye-opening experience for me as an undergraduate student. It not only provided me an invaluable opportunity to acquire knowledge in processing and visualizing data with some up-to-date models and packages in supervised and
unsupervised machine learning such as Naive Bayes, random forest, and wordfish, but also offered me an interactive platform to exchange ideas with postgraduate and Ph.D. senpais who were conducting research around various topics in social science. Reflecting on Tokyo’s humid summer in 2019, I believe that this one-week course opened a door for my passion to continuously sharpen my hands-on software skills in the R programming language and gave me a comprehensive understanding of how computer science has indeed been revolutionizing the recent political science landscape. I would like to express my deep gratitude to the instructor, Dr. Nicole Baerg, for vividly explaining each concept in machine learning that seemed complicated at first glance and for patiently diagnosing our codes when something went south. Now that I am going to advance to graduate school, I plan to apply the state-of-the-art statistical methods I learned from this course to my own research surrounding political values and public opinions in East Asian societies through utilizing and interpreting panel data obtained from cross-regional survey projects. I also would like to register for other courses in the Essex Summer School in the near future to keep myself updated with helpful classification and scaling techniques during the progress of my master’s thesis.
Peter (Siyuan) Chai, 4th Year Undergraduate Student and Research Assistant, School of Political Science and Economics, Waseda University
– 3B Quantitative Text Analysis (Dr. Nicole Baerg)
In my training as a psychologist I was only taught frequentist statistics, while I eventually figured out that I need a different kind of statistics: Bayesian statistics. I have followed Richard Morey on Twitter for a long while, and read his papers and blogs. That made me decide to take his course in Bayesian statistics. He is a great teacher and I learned a lot from his course, although I still need to learn much more.
– 3F Bayesian Analysis for the Social and Behavioural Sciences (Richard Morey)
I have used a method we learned at ESS in an article and I succeeded in publishing it in a high-ranked journal. I used Thematic Analysis in the course with Prof. Lea Sgier, the course was amazing and I had a great time… Thanks a lot for your efforts to make ESS a success.
– 1H Qualitative Data Analysis: Methodologies for Analysing Text and Talk (Lea Sgier)
I got published this summer entirely thanks to the skills I learned in the structural equations class at Essex in 2014 …Professor Schmidt and his teaching team were incredibly supportive. Thanks to them, I was able to write this paper even though there was no one with expertise in structural equations in my department. I really want to extend deep thanks to them.
– 3I Factor Analysis & Structural Equation Modelling with MPLUS (Peter Schmidt)
