Undergraduate
Programs
Overview
Statistics is a core tool for data-driven decision-making and plays an essential role across a wide range of academic and industrial fields.
In the era of big data, statistics has established itself as a powerful discipline that not only analyzes numbers, but also uncovers patterns, forecasts the future, and derives optimal strategies.
Our department, in line with these societal changes, seeks to cultivate data analysis experts with both theoretical depth and practical skills through its curriculum.
Fundamentals of Statistical Theory
Learn the concepts of probability and statistics and acquire basic methods of data collection and analysis.
Advanced Statistical Theory
Gain a deeper understanding of the mathematical foundations and applications of statistical techniques through advanced theory.
Applied Statistics
Learn practice-oriented analytical methods such as quality control, insurance, experimental design, and data mining, based on statistical reasoning.
Data Science Courses
Acquire cutting-edge skills in deep learning, natural language processing, and image analysis to build problem-solving capacity for real-world challenges in the age of AI and big data.
Program Requirements
Classes of 2018–2025
| Category | Courses | Credits | Requirements | Notes |
|---|---|---|---|---|
| General Education | Includes common, core, and elective general education courses | 31 | Up to 45 credits may be counted toward graduation | If more than 45 credits are taken, the excess will be deducted from the 132 total graduation credits |
| Basic Major | Introduction to Statistics (1) Introduction to Statistics (2) Statistical Mathematics (1) Statistical Mathematics (2) |
12 | Basic Major course credits are not counted toward the major credit requirement | |
| Required Major | Mathematical Statistics (1) Mathematical Statistics (2) Regression Analysis Multivariate Statistical Analysis |
12 | Required Major course credits are counted toward the major credit requirement | |
| Major | 66 credits: Intensive Major 45 credits: Double Major, Interdisciplinary Major, Convergence Major, Student-Designed Major |
Students pursuing a Minor must complete at least one among Intensive, Double, Interdisciplinary, Convergence, or Student-Designed Major | ||
| Free Electives | Free selection | |||
| Total | 132 | Minimum of 132 total credits and a cumulative GPA of 2.0 or higher required for graduation |
Double Major and Minor Requirements
1. Double Major in Applied Statistics (for students from other departments)
- 12 credits in Basic Major Courses (Statistical Mathematics (1), (2); Introduction to Statistics (1), (2)) – counted as “Free Electives.”
- 12 credits in Required Major Courses (Mathematical Statistics (1), (2); Regression Analysis; Multivariate Statistical Analysis) – counted as “Double Major.”
- A total of 45 credits required, including Major Required.
2. Minor in Applied Statistics (for students from other departments)
- At least 21 credits, including a minimum of 6 credits from Major Required courses (any courses).