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Statistics

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

교육과정
Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
STA2017 Matrix algebra for statistics 3 3 Major Bachelor 2-3 Korean Yes
This course is a basic course for undergraduate students in statistics to provide useful and practical theory in matrix and linear algebra. We will start with basic operations such as addition, multiplication, trace and transpose of matrices and will discuss how to calculate determinants and inverse of matrix. We will further understand matrix algebra by introducing axiomatic linear algebra theory. For intermediate topics, we will introduce differentiation of matrix and matrix decomposition. Such basic knowledge will be applied to derive basic probability distributions. Finally, multiple regression will be illustrated by matrix algebra.
STA3001 Introduction to Time Series Analysis 3 6 Major Bachelor 3-4 Korean Yes
Basic concepts of time series are presented, including stationarity, causality, invertibility, autoregressive moving average models, and forecasting. Methods for building AR, MA and ARMA models are discussed. The course also introduces ARIMA models, and briefly touches on state space models and the Kalman filter. Real-world data are used as illustrative examples.
STA3003 Introduction to Statistical Inferences 3 6 Major Bachelor 3-4 English,Korean Yes
Introduction to basic concepts and idea of estimation and hypotheses testing which are necessary to statistical decision making. Emphasis on point estimations, interval estimations and classical test procedures and practice with real examples will be provided.
STA3005 Introduction to Bayesian Statistics 3 6 Major Bachelor 3-4 English Yes
This course is an introduction to practical Bayesian methodology. The use of conjugate families, introduced in Intermediate Statistics is discussed. The emphasis throughout is on the application of Bayesian thinking to problems in data analysis.
STA3007 Statistical Simulation 3 6 Major Bachelor 3-4 English Yes
Generation of uniform and nonuniform random numbers, discrete event simulations, simulation languages, design of simulations, statistical analysis of the output of simulations, applications to modeling stochastic systems in computer science, engineering, and operations research.
STA3008 Introduction to Multivariate Statistical Analysis 3 6 Major Bachelor 3-4 Korean Yes
Introduction to multivariate statistical analysis; statistical methods for analyzing and displaying multivariate data: dynamic graphics, principal components, factor analysis, canonical correlations, cluster analysis, classification methods, Hotelling's T2, multivariate analysis of variance.
STA3010 Introduction to Nonparametric Statistics 3 6 Major Bachelor 3-4 Korean Yes
Introduction to nonparametric problems; tests based upon sample distribution functions, rank tests for location, scale and independence; local properties of rank tests.
STA3011 Introduction to Biostatistics 3 6 Major Bachelor 3-4 - No
Statistical methods useful for biostatistical problems. Topics include analysis of observational studies and randomized clinical trials, techniques in the analysis of survival and longitudinal data, approaches to handling missing data, and meta-analysis. Examples will come from recent studies in cancer, AIDS, heart disease and psychiatry and from studies to evaluate health care.
STA3012 Categorical Data Analysis 3 6 Major Bachelor 3-4 Korean Yes
The objective is to provide theory and methods for analysis of cross-classified categorical data. The main subject areas are descriptive and inferential statistics for two-way contingency tables, logistic regression, loglinear and logit methods for multidimensional tables, models for ordinal categorical data, and maximum likelihood and asymptotic theory for models for categorical variables.
STA3014 Statistical Data Mining 3 6 Major Bachelor 3-4 Korean Yes
The explosive growth of many business, government, and scientific databases has far outpaced our ability to interpret and digest this data, creating a need for a new generation of tools and techniques for automated and intelligent database analysis. These tools and techniques are the subject of this course and it includes Market Basket Analysis, Clustering, Link Analysis, Decision trees, and Artificial Neural Networks, etc.
STA3017 Introduction to Survival Analysis 3 6 Major Bachelor 3-4 English Yes
Introduction to concepts and techniques used in the analysis of time to event data, including censoring, hazard rates, estimation of survival curves, parametric and nonparametric models, regression techniques, regression diagnostics.
STA3018 Insurance Statistics 3 6 Major Bachelor 3-4 Korean Yes
Introduction to Statistical theories and techniques to calculate insurance fee and insurance plans. Learn mathematical statistics tools to calculate life-table, survival function and other relevant statistics useful to determine insurance fee and plans.
STA3020 Introduction to Financial Statistics 3 3 Major Bachelor 3-4 Korean Yes
This is an introductory course for statistical theory and methods for financial area including bank and securities. Topics included are risk management, volatility and pricing of derivatives, loss function inferences, parameter estimation for PER, statistical marketing techniques, and extreme value theory.
STA3021 An Introduction to Stochastic Processes 3 3 Major Bachelor 3-4 English Yes
This course aims at a gentle introduction to stochastic process. Stochastic process refers to probabilistic modelling of underlying dynamics evolving either by time or space. We will study discrete stochastic processes first and then extend it to continuous case. For example, Poisson process and its extension to renewal process will be studied first. Then, the celebrated Markov Chain will be discussed intensively. For continuous stochastic processes, random walk and Brownian motion will be covered and brief introduction to stationary process will be provided.
STA3025 Sampling Theory 3 6 Major Bachelor 3-4 - No
This course aims for a gentle introduction to sampling theory. Major topics include simple random sampling, stratified sampling, stratified random sample, systematic sampling, double sampling and lots of real life applications such as sample size determinations will be discussed. Missing values are also discussed in this course.