Korea University Department of Statistics

▶▶▶ Suggested Courses by Year

+: Courses offered every semester

*: Required courses

**: SAMPLING THEORY (STAT311) becomes an elective course for students who enrolled in or after 2016. For students who enrolled before 2016 and whose double and dual major in Statistics or transfer to the Department of Statistics (undergraduate) began after the 2015 fall semester, this course is considered a required course. This course is only offered in the fall semester starting from 2017.

***: The course number of STATISTICAL RESEARCH will change from STAT160 to STAT161 from the 2017 spring semester. If a student who has taken STATISTICAL RESEARCH (STAT160) takes STATISTICAL RESEARCH (STAT161), it is considered a course retake.

▶STATISTICAL RESEARCH (STAT161) 통계적탐구

This is a course designed to teach freshmen in the College of Political Science and Economics empirical research methods for studying society, such as sample surveys and experiments, relevant measurement problems, data description methods, the exploration of relationships between variables, the concept of probability, and statistical inference. The major concepts of statistics will be taught without relying on mathematics. 

▶ ELEMENTARY STATISTICS (STAT170) 기초통계학 

In this course, the basic concepts of statistics are explained through examples, and skills to apply statistics to various fields are studied.

▶ STATISTICAL MATHEMATICS (STAT201) 통계수학 

This course covers calculus as basic mathematics required for statistics, fundamental analysis including the set theory, and linear algebra. 

▶ 통계계산소프트웨어 (STAT180, 2017~) / 

ELEMENTARY COMPUTATIONAL STATISTICS (STAT202, ~2016) 기초전산통계

This course introduces and provides actual training in methods for effectively using statistical package programs.

▶ 통계계산프로그래밍 (STAT204, 2017~) / 

INTRODUCTION TO STATISTICAL PROGRAMMING (STAT203, ~2016) 통계프로그래밍입문 

This course covers concepts and applications of statistical programming using the latest computer languages.

▶ INTRODUCTION TO PROBABILITY THEORY (STAT221) 확률론입문 

This course introduces the concepts of probability and probabilistic thinking and various probability models that are fundamental to statistics. It also covers expectation value, moment generation functions, and probability distribution theories, including conditional distribution theory, as well as limit theorems.

▶ MATHEMATICAL STATISTICS (STAT232) 수리통계학 

This course logically develops and interprets the mathematical basis of statistics including stochastic variables, variable transformation, sampling distributions, and the estimation and testing of hypotheses.

▶ MATRIX THEORY (STAT241) 행렬이론 

This course introduces the concepts and techniques of matrix algebra and explains its statistical applications. Topics include determinants, inverse matrices, eigenvalues and eigenvectors, and singular value decomposition. 

▶ STATISTICAL METHOD IN SOCIAL SCIENCE (STAT242) 사회과학을위한통계적방법

This course covers statistical methodologies, such as statistical data exploration, the concept of statistical inference, the planning and analysis of comparative experiments, categorical data analysis, and the reliability and validity of measurements. 

▶ TIME SERIES ANALYSIS (STAT302) 시계열분석 

This course introduces statistical techniques for time series data analysis including ARIMA analysis, transfer function analysis, and intervention analysis. Students will practice using statistical package programs. 

▶ SAMPLING THEORY (STAT311) 통계조사론입문 

This course covers the fundamental principles of sampling surveys, optimal sampling methods that minimize sampling error through design procedures, and their consequential reasoning. It also examines the causes of non-sampling errors and methods to control for them.

▶ STATISTICAL DATABASE (STAT312) 통계데이터베이스 

This course covers the construction and utilization of databases to manage and consult large sample data.

▶ 통계계산방법 (STAT323, 2017~) / 

COMPUTATIONAL STATISTICS (STAT321, ~2016) 중급전산통계 

This course follows ELEMENTARY COMPUTATIONAL STATISTICS. It introduces the theoretical background of numerical interpretation required for statistics computation and provides actual training in statistical programming languages.

▶ NON-PARAMETRIC STATISTICS (STAT332) 비모수통계학 

This course introduces non-parametric statistical methods and applies them to real-life problems, including non-parametric correlation coefficients, non-parametric ANOVA, regression analysis, and the analysis of contingency tables.

▶ EXPERIMENTAL DESIGN METHOD (STAT341) 실험계획법 

This course introduces basic concepts of experimental design and various methods, including completely randomized design, randomized blocking design, Latin square design, factorial experiments, split plot design, fractional replication, and response surface design.

▶ REGRESSION ANALYSIS (STAT342) 회귀분석 

This course covers the setting, fitting, and diagnosis of regression models, including simple linear regression, multivariate linear regression, variable selection, and non-linear regression. Students will use statistical package programs such as SAS.

▶ CATEGORICAL DATA ANALYSIS (STAT343) 범주형자료분석 

This course is about analyzing categorical data using the analysis of contingency tables, logit models, and log-linear models.

▶ ACTUARIAL STATISTICS (STAT344) 보험통계학 

This course focuses on methodologies applicable to the field of insurance, including interest theory, basic and general pensions, survival distribution and life tables, life insurance, life annuities, and net premiums.

▶ INTERNSHIP FOR PRACTICAL EDUCATION I (STAT375) 글로벌통계실무교육인턴십I

This course is designed to train students to become internationally competent professionals in statistics by providing field experience in domestic and international institutions or businesses.

▶ MUTIVARIATE STATISTICAL ANALYSIS (STAT401) 다변량통계분석 

This course covers statistical methods for multivariate data analysis, including multivariate normal distributions, multivariate linear models, and principal component, factor, canonical correlation, discriminant, and cluster analyses.

▶ INTRODUCTION TO DATA MINING (STAT402) 데이터마이닝입문 

Using supervised and unsupervised learning methods of data mining, students will learn how to generate effective knowledge and also study and practice rational decision-making processes.

▶ EXPLORATORY DATA ANALYSIS (STAT406) 탐색적데이터분석 

This course introduces techniques of exploratory data analysis (EDA) for determining data structure and characteristics. Specific topics include stem-and-leaf plots, data transformation with boxplots, scatter plots, smoothing methods, median smoothing, and graphic methods for multivariate data.

▶ ECONOMETRIC ANALYSIS (STAT411) 경영경제데이터분석 

This course introduces statistical methods used in heteroscedasticity, and the panel data, structure equation, and discrete data analyses that are commonly used in econometric data.

▶ TOPICS IN MATHEMATICAL STATISTICS (STAT412) 수리통계학특강 

This course is an advanced level mathematical statistics course that focuses on advanced theories in statistical inference.

▶ FINANCIAL STATISTICS (STAT413) 금융통계학 

This course introduces theories of option pricing, an important area in financial engineering. Topics include pricing through the geometric Brownian motion process and interest rates, no-arbitrage principle, Black-Scholes model and formula, and Monte Carlo simulations.

▶ LAW AND STATISTICS (STAT419) 법과통계학 

This course covers various statistical methods to analyze surveys and experimental or observational data provided by the interested party and to evaluate empirical evidence in legal disputes.

▶ BIO-STATISTICS (STAT421) 생명과학데이터분석 

This course introduces statistical methods used in the field of life sciences including biology, medical science and pharmacology. It covers sectional, cohort, and patient-comparative studies, matching and standardization, survival analysis, log-linear models, and logistic regressions.

▶ STATISTICS SEMINAR (STAT422) 통계논문세미나 

Major statistical issues are studied and discussed based on research papers.

▶ TOPICS IN STATISTICS (STAT431) 통계학특강 

This course explains and teaches major topics in statistics. 

▶ LINEAR METHODOLOGY (STAT443) 선형방법론

Through this course, students will learn linear methodologies based on matrix algebra and basic statistical theories. Linear algebra and statistical theories are discussed, and based on this, the representative linear method, which involves the estimation, verification, model diagnosis, and variable selection of the multiple linear regression model, is theoretically studied. In addition, logistic regression analysis and spline methodology are also introduced from the perspective of linear methodologies.