Yonsei News

In our daily lives, we constantly encounter data—from sports game records and lottery results to clinical trials, opinion polls, and weather forecasts. Many of these elements are types of data that can be studied in the field of statistics. Statistics is not simply about analyzing numbers or creating graphs; it is a discipline that extracts important information from complex data and uses it to predict the future or enable decision-making. For example, determining whether a new drug is effective or deciding the optimal height of a levee to prevent flood damage are situations where statistics plays a vital role.

To address life’s various challenges statistically, accurate data collection and proper analytical skills are essential. Therefore, Applied Statistics employs a range of scientific tools such as mathematical modeling, data analysis methodologies, and machine learning/deep learning techniques.

What specific courses are taught in the Department of Applied Statistics? What research areas are commonly explored? What unique characteristics define Yonsei University's Department of Applied Statistics? To answer these questions and learn everything about the department, we spoke to the department chair, Professor Kang Sang-wook.

Q. What role does statistics play in the era of big data?

Today, we often hear the term "big data," which refers to extensive data generated every moment from sources such as the internet and social media. These vast and unstructured data lose their significance, if they are not properly analyzed and used. This is where statistics plays a crucial role, helping us analyze the data to extract valuable information.

For instance, every online search we perform or purchase we make is stored as data. However, merely collecting this enormous data hold inadequate meaning. It is essential to analyze the data correctly and identify the useful information within. This task is performed under the field of Applied Statistics. Thus, applied statistics goes beyond simply handling data; it plays a crucial role in solving the many challenges we face in the era of big data.

 Q. Data and sampling are crucial to derive effective statistics. In the era of big data and AI, how can we address data bias?

Addressing data bias is critical to ensuring accurate results. If biased data are used incorrectly, they can lead to false conclusions and even cause social or ethical issues. The most ideal way to solve data bias is to consider potential biases from the data collection stage, to ensure that data are gathered without inherent skew.

For experimental data, bias can be easily mitigated through proper experimental design. This is why well-planned experimental design is essential, and the field of statistics that deals with these principles is called Design of Experiments (DOE).

For observational data, removing bias can be more challenging. Although efforts should be exercised to minimize bias during data collection, if unavoidable biases occur, they can be corrected by collecting additional data or using data augmentation techniques. Alternatively, reducing the overrepresentation of certain data can help balance the dataset.

These processes are often addressed in fields such as causal inference and data integration. Accordingly, this topic has received significant attention from scholars in the big data era, making it a critical area of study today.
 
In AI models, when calculating the objective function, the contribution of the data can be adjusted based on distribution. Moreover, model bias can be analyzed and corrected in post-processing to improve the model’s reliability. This is one of the key areas actively researched in the AI field. Additionally, methods are being developed to perform post-training using reinforcement learning based on human feedback, ensuring that unwanted outputs are minimized.

Q. What courses are typically offered in the Department of Applied Statistics?

Required courses include Calculus, Linear Algebra, Programming, and Mathematical Statistics, which serve as the foundation for more advanced subjects. Students who wish to explore the field of statistics in-depth can select from courses such as Regression Analysis, Survival Data Analysis, Bayesian Statistics, Actuarial Statistics, Nonparametric Statistics, and Statistical Machine Learning to learn how statistics is applied in various fields.
For those interested in specializing in Data Science, there are a wide range of courses available, including Data Mining, Deep Learning, Information Theory, Data Structures, Reinforcement Learning, Computer Vision, and Quantum Machine Learning.
 
Many types of software are used for data analysis, each suited to different purposes. Among these, R and Python are highly flexible and widely used in both academic and industrial research because they are open source. R is particularly specialized for statistical analysis, whereas Python is popular in machine learning. SPSS and SAS do not require direct programming, simplifying them for non-specialists to use, although they come with licensing fees and are primarily employed for commercial purposes.

Q. What are the strengths and potential of our university's Department of Applied Statistics?

The Department of Applied Statistics, founded in 1967, is one of the oldest in Korea and has developed into the largest department of its type, with 19 faculty members. By 2025, we will expand to 21 professors, making it the only statistics department in the country with such a large faculty. Our team includes leading experts in diverse areas of data science, including big data analysis, machine learning, artificial intelligence, quantum information science, medical and biostatistics, and financial statistics. This breadth demonstrates that our department not only covers traditional areas such as statistical inference but also advances into cutting-edge, strategic fields.

Our education and research span specialized fields such as Bayesian statistics, data mining, Monte Carlo methods, survival analysis, medical statistics, functional data analysis, and actuarial statistics. We are also pioneers in big data and AI research, key drivers of the Fourth Industrial Revolution, responding to society's increasing need for data-driven decision-making.

The department’s programs prepare students for a wide range of careers in finance, semiconductors, telecommunications, retail, insurance, and medicine. The broad career paths available to our graduates reflect this preparation. We also offer courses linked to economics and business to further enhance students’ career prospects in various fields.

Our alumni association actively supports the department through initiatives such as remodeling Daewoo Hall and providing development funds. Alumni contribute to student activities such as athletic events and school trips, and the College of Commerce is known for its strong alumni network. Graduates excel in fields such as academia, finance, accounting, credit rating, public institutions, semiconductors, IT, pharmaceuticals, retail, and consulting. This extensive network offers valuable support to students and graduates for employment, further studies, research collaboration, and information exchange.

 Q. What is the current status of enrolled students? Please introduce major departmental events and student activities.

As of the second semester of 2024, there are over 300 undergraduate students and around 130 graduate students enrolled in the Department of Applied Statistics. The average enrollment in courses offered by the department has been consistently high, with 70.2 students in 2022, 76.4 in 2023, and 59.7 in 2024, making it one of the most popular departments on campus. The flexibility of applied statistics allows for its application and extension across various academic fields, resulting in a significant number of students from other departments also enrolling in our courses, with 40-50% of students in many subjects coming from outside the department.
 
Key student activities in our department include the opening ceremony, statistical meetings, snack events, mini competitions with the Korea University Statistics Department, AS Day, sports events with the graduate program in Statistics and Data Science, the AS Textbook Market, study groups for major subjects, mentoring programs for double major students, a booth at the university festival, and various student council activities. Additionally, we have interest groups such as the band SVAN, a badminton club called TURNS, a soccer group named CLT, a fishing club called EUNG-E, and the Yonsei Sports Analytics Lab (YSAL).

A notable initiative is the Group Meeting that began in 2023, where small groups of 4-5 students from different year groups are paired to enhance friendships and share interests each semester. We maintain a consistent relationship with Korea University’s Statistics Department, holding a face-to-face meeting in the first semester and a mini sports competition in the second semester each year. To foster interaction between undergraduate and graduate students, we host annual sports competitions at the university's athletic field and sports science center.

The “AS Textbook Market,” a student-run initiative in the Department of Applied Statistics, allows seniors to pass down their textbooks to juniors at prices 60% or lower than the original cost. This project exemplifies the close-knit community within the department, where seniors actively support the next generation. Additionally, to help students become more proficient in statistics, study groups for reviewing and preparing for major courses are held during breaks. Under the “Dual Major Mentor-Mentee Matching” program, students with a second major share their experiences and expertise with those exploring different domains of statistical application.

The Yonsei Sports Analytics Lab (YSAL) is a student association dedicated to analyzing sports data by applying statistical methods. The club fosters students' skills in sports data analysis and is committed to developing innovative approaches to sports analytics. YSAL operates with the aim of collaborating with both campus and professional sports teams and is currently working with the professional basketball team, Samsung Thunders.

Through such diverse student activities, the Department of Applied Statistics cultivates strong bonds between classmates and between seniors and juniors. These activities help students not only grow academically, but also become expert professionals who can provide accurate, data-driven solutions to real-world problems.

Q. Why is the graduate program called the Department of Statistics and Data Science, while the undergraduate program has a different name?

In 2020, the graduate program changed its name from the Department of Applied Statistics to the Department of Statistics and Data Science to strengthen education in the field of data science. Following this change, many new data science-related courses were introduced to enhance the curriculum. For the master’s program, students are now admitted into two distinct specializations: Statistics and Data Science. As of the second semester of 2024, the department has 14 Ph.D. students, 27 in the integrated program, and 96 master’s students.

The Department of Statistics and Data Science is the only department in Korea to manage a large-scale BK21 project group. Since September 2020, it has led innovative education in data science through the "Big Data-Based Convergent Data Science Education and Research" project. Most of the department’s faculty participate in this initiative, providing scholarships and research support to graduate students, thereby fostering world-class research talent. Moreover, the program promotes international collaboration and aims to set new paradigms in data science. In 2024, the department was recognized as an outstanding educational and research group in the BK21 Innovation Talent Project's performance evaluation.

By successfully integrating statistics and data science, the department is continuously expanding its academic boundaries and creating new value. These efforts have received academic recognition both domestically and internationally, while also making significant societal contributions.

"Through the education provided by the Department of Applied Statistics, I expect students will develop essential data literacy for the big data era and, based on this, be able to extract accurate signals from extensive data."

Professor Sangwook Kang

"My research focuses on data with temporal or spatial correlations. I am primarily engaged in developing new models and algorithms that explain such data."

Professor Jaewoo Park

"Although data is constantly being generated and accumulated in all aspects of daily life, proper exploration and analysis are essential to make accurate decisions based on it. The Department of Applied Statistics enables such data-driven decision-making."

Professor Taeyoung Park

"I conduct research on information theory and machine learning while nurturing the next generation of talent in these fields. My goal is to design data science technologies that are mathematically sound and beneficial to society."

Professor Jy-yong Son

"The Department of Applied Statistics and the Department of Statistics and Data Science are at the forefront of developing highly reliable AI algorithms that are both theoretically grounded and perform exceptionally well in practice."

Professor Kyungwoo Song

"The Department of Applied Statistics and the Department of Statistics and Data Science foster the ability to solve complex problems through statistical thinking and data analysis. Here, students can grow into experts capable of driving real-world changes across various fields by leveraging data."

Professor Chi Hyun Lee

"Through the curriculum of the Department of Applied Statistics, I expect students can acquire a deep understanding of the fundamental principles of statistical methodologies, learn to implement and apply various models, and develop comprehensive data science skills, including data engineering and problem-solving."

Professor Yongho Jeon