College of Economics | Academic Programs | Departments | Statistics

For more details on the courses, please refer to the Course Catalog

교육과정
Code	Course Title	Credit	Learning Time	Division	Degree	Grade	Language	Availability
STA5024	Statistical Inferences	3	6	Major	Master/Doctor	1-4	Korean	Yes
Advanced topics for statistical inferences including theories of estimation and hypotheses test which are necessary in statistical decision making are studied. Concepts of the point and interval estimations, and some methods to obtain the minimum variance unbiased estimator are also explained based on various properties of point estimators, Moreover, most powerful test, generalized likelihood ratio test, goodness-of-fit test, sequential likelihood ratio tests, and nonparametric estimation are discussed.
STA5025	Statistical Consulting	3	6	Major	Master/Doctor	1-4	-	No
Participants will work on problems arising in the consulting service and will discuss general ways of handling such problems. There will be working sessions with researchers in substantive fields and occasional lectures on consulting.
STA5028	Probability Theory	3	6	Major	Master/Doctor	1-4	-	No
This course covers measure and probability spaces; random variables; distribution functions; abstract Lebesgue and Lebesgue-Stieltjes integration; monotone, dominated, Cauchy, and mean convergence; Fubini and Randon-Nikodym theorems, zero-one laws.
STA5029	Advanced Statistical Computing	3	6	Major	Master/Doctor	1-4	-	No
Selected topics from general statistical computing area. Review current issues and literatures of selected area and try to predict future directions and develop new theories.
STA5030	Bayesian Statistics	3	6	Major	Master/Doctor	1-4	Korean	Yes
Conjugate priors; comparision of Bayesian and classical theories; process, models, and techniques to obtain posterior distributions; hierarchical Bayes; empirical Bayes.
STA5031	Design and Analysis of Experiments	3	6	Major	Master/Doctor	1-4	-	No
Construction and analysis of multifactor designs, factorials, fractional factorials, balanced incomplete block designs, Latin squares, orthogonal arrays of strength d and response surface designs. Fractionating mixed level factorials, confounding and blocking techniques, study of robustness of designs to loss of design point.
STA5034	Mixture models	3	6	Major	Master/Doctor	3-8	-	No
This course focuses on model-based clustering methods using finite mixture modeling. This course introduces theoretical aspects of mixture (or latent class) models, the EM algorithm as a computational tool, and some potential applications. Students learn descriptive features of general mixture models, mixture of exponential families, geometry of multinomial mixtures, latent class analysis, and algorithmic theory for the EM algorithm in mixture models.
STA5035	Longitudinal Data Analysis	3	6	Major	Master/Doctor	3-8	Korean	Yes
This is an introductory course in longitudinal data analysis for graduate student in the department of Statistics. This course will cover various statistical models and statistical inference for correlated outcome variables with a special emphasis on repeated measurements in medical and social studies.
STA5036	Advanced time series analysis	3	6	Major	Master/Doctor	1-4	Korean	Yes
Recent advances in time series analysis such as high dimensional time series models and nonlinear time series models are discussed with latest research papers. This course requires paper readings, presentations and real data analysis projects.
STA5037	Topics in Applied Statistics	3	6	Major	Master/Doctor	3-8	-	No
This course is about learning various latest statistical techniques and apply them to real applications. We will start with studying related books, papers and then apply them to real data applications. This course is encouraged to take for more advanced study of statistical methodologies, in turn it requires active participation over the courses including several in-class presentations and real data analysis projects.
STA5038	Large sample theory	3	6	Major	Master/Doctor	1-4	-	No
This course mainly covers various statistical theory including probability and large sample theory under various settings. Specifically, it include modes of convergence, basic statistical large sample theory, rank statistics, and asymptotic theory of various estimators. In this course, students will learn various statistical properties based on rigorous theoretical analysis. The ultimate goal of this course is that students have attitudes and analytical skills required for statistician.
STA5039	Causal Inference	3	6	Major	Master/Doctor		Korean	Yes
This course will cover various statistical methods of causal inference, with a focus on design and analysis of observational studies. Topics will include potential outcomes; randomized experiments; confounding; observational studies; matching, weighting, propensity score methods for controlling confounding in observational studies; double robustness; unmeasured confounding bias; sensitivity analysis; instrumental variables. Prerequisite: STA5005 (Mathematical Statistics), or equivalent graduate-level coursework on the theory of statistics.
STA5040	Topics in Deep Learning	3	6	Major	Master/Doctor		Korean	Yes
This course surveys a wide variety of recent advanced topics in deep learning. After learning the concepts and basic theories of various methods and models used in deep learning, grasp the flow of the latest topics in the deep learning field, discover new research topics, and use them as the basis for research.
STA5041	Topics in Bayesian Methods	3	6	Major	Master/Doctor		-	No
Our overall goal is to learn a decent set of Bayesian methods in many applications. The topics covered in this class include Bayesian ensemble trees model, Bayesian nonparametric methods for clustering and density estimation, several Bayesian variable selection methods, and Bayesian spatial data analysis and its extension towards image data processing. In addition, R and Rcpp will be used to implement the methods list above.