Graduate Program

Department of Statistics and Actuarial Science at Soongsil University is the only department in Korea, which has both
an statistics tract that develops data analysis capabilities which are core competencies of the future society and
an actuarial science track that maximizes the synergy between statistics and actuarial science.

Curriculum (Credit: 3 credits / Time: 3 hours)

Major Code Subject
Common 21603203 Mathematical Statistics I
21603205 Stochastic Processes I
21603245 Multivariate Statistical Analysis I
21603246 Time Series Analysis I
21603212 Linear Models I
21603215 Mathematical Statistics II
21603224 Linear Models II
21603233 Survival Analysis
21603242 Seminar in Statistics I
21603243 Seminar in Statistics II
21603244 Seminar in Statistics III
Statistics 21603204 Probability Theory I
21603206 Regression analysis
21603207 Experimental Design
21603209 Sampling Theory
21603211 Nonparametric Statistics
21603213 Statistical Consulting I
21603214 Statistical Consulting II
21603216 Probability Theory II
21603217 Stochastic Processes II
21603218 Statistical Decision Theory
21603219 Testing Statistical Hypotheses
21603220 Asymptotic Theory
21603221 Seminar in Theorectical Statistics I
21603222 Seminar in Theorectical Statistics II
21603223 Statistical Computing I
21603225 Nonlinear Models
21603226 Applied Probability Theory I
21603227 Applied Probability Theory II
21603231 Seminar in Applied Statistics I
21603232 Seminar in Applied Statistics II
21603234 Optimization Theory
21603235 Bayesian Statistics
21603236 Multivariate Statistical Analysis II
21603237 Time Series Analysis II
21603238 Statistical Computing II
21603239 Information Theory
21603240 Statistical Quality Control
21603241 Data Mining
Insurance 21603267 Life Actuarial Mathematics I
21603268 Life Actuarial Mathematics II
21603269 Non-Life Actuarial Mathematics I
21603253 Principles of Insurance
21603247 Seminar in Actuarial Science I
21603255 Pension Mathematics
21603248 Financial Mathmatics I
21603264 Financial Mathmatics II
21603270 Non-Life Actuarial Mathematics II
21603258 Seminar in Actuarial Science II
21603259 Financial Econometrics
21603260 Actuarial Risk Management
21603262 Asset Liability Management
21603263 Financial Engineering
21603265 Life Insurance Product Development
21603266 Actuarial Science for Health Insurance
50084019 Stochastic Calculus for Finance

Master’s Course Opening for Each Semester

Master’s Course First Semester Second Semester
Statistics Major Actuarial Science Major Statistics Major Actuarial Science Major
1st Year Mathematical Statistics I
Financial Mathmatics I
Regression Analysis
Mathematical Statistics I
Financial Mathmatics I
Non-Life Actuarial Mathematics I
Linear Models I
(Multivariate Statistical Analysis I, Statistical Computing I, Stochastic Processes I)
Life Actuarial MathematicsI
Financial Mathmatics II
Non-Life Actuarial Mathematics II
2nd Year Data Mining
(1 subject among Time Series Analysis and Bayesian Statistics)
Life Actuarial Mathematics II
(1 subject among Pension Mathematics, Actuatial Risk Management, Life insurance product development, Principles of Insurance, Seminar in Actuarial Science I)

Subject Outline - Statistics Major

Mathematical Statistics I
This subject deals with mathematical theories common to statistical application methodologies, which covers distribution theory, and estimation theory. This lecture covers various distributions, limit distributions, sufficiency and exponential families, various estimation methods including maximum likelihood estimation, and selection criteria for good estimators.
Regression Analysis
This course reviews basic contents such as simple regression and multiple regression analysis, and deals with problems such as residual analysis, model selection method, influence measurement, and multicollinearity search and resolution. It further looks into weighted regression, variable transformation problems, nonlinear regression, and nonparametric regression analysis for cases that deviate from general assumptions.
Linear Models I)
This subject introduces generalized linear models and discusses logistic regression models and log-linear models for frequency data, in terms of the generalized linear model.
Multivariate Statistical Analysis I)
This subject studies multivariate statistical analysis based on multivariate statistical theory. It introduces the multivariate normal distribution and uses it to study inference and hypothesis testing on the mean vector and covariance matrix. It also studies principal component analysis, factor analysis, canonical correlation variance, discriminant analysis, and cluster analysis using multivariate covariance structure. It conducts data processing practice using statistical packages.
Statistical Computing I
This subject studies numerical analytical methods to obtain quick solutions while reducing calculation errors of various statistical calculations. It deals with random number generation, algorithms for linear and nonlinear models, and software analysis using them.
Stochastic Processes I)
This subject is statistical theory about probabilistic events that occur over time. This lecture covers the contents of the Markov chain, Poisson process, regeneration process, martingale, etc.
Data Mining
This subject studies various mathematical and statistical models of data mining. This lecture covers computer learning systems, Bayesian decision-making, latent Markov models, parametric or non-parametric classification analysis, cluster analysis, neural network networks, evolutionary algorithms, and multi-dimensional reduction.
Time Series Analysis I
This subject studies the Box-Jenkins model for time series data. This lecture studies the moving average model, auto regression model, ARIMA model, and it discusses the identification, estimation, distinction, and prediction methods of these models.
Bayesian Statistics
This subject deals with Bayesian inference based on Bayesian decision theory. It deals with subjective probability, prior distribution, likelihood principle, predictive distribution, and Bayesian theories related to estimation, test, and regression analysis.

Subject Outline - Actuarial Science Major

Financial Mathmatics I
This lecture covers simple and compound interest methods, and the calculation of the present and closing prices of defined annuities. It deals with topics such as internal rate of return, amortization, sinking funds, and bond valuation.
Non-Life Actuarial Mathematics I
This lecture introduces basic actuarial theory and techniques related to indemnity insurance. It deals with topics such as characteristics of each indemnity insurance item, rate-related statistical data accumulation and management, basic rate determination, rate classification system composition method, risk premium, basic insurance premium calculation method, and long-term indemnity insurance settlement.
Life Actuarial Mathematics I
This lecture introduces actuarial theory and techniques related to life insurance. It covers topics such as interest theory, survival distribution model and experience life table, net premium, life annuity, installment premium, and liability reserve.
Financial Mathematics II
This lecture provides an overview of derivatives. It introduces various types of derivative products such as futures, options, and swaps, and covers topics such as investment strategies, valuation methods, and risk management techniques.
Non-Life Actuarial Mathematics II
This lecture introduces advanced actuarial theory and techniques related to indemnity insurance. It covers topics such as the reserve estimation method, the composition and evaluation method of the experience rate system, the application method of the reliability method, the project cost estimation method, the profit and loss evaluation method, the mathematical underwriting method, and various simulation evaluation methods.
Life Actuarial Mathematics II
Following the life Actuarial Mathematics I, this lecture covers various theories related to joint life insurance, multiple decremental tables, the basics of pension mathematics, business insurance premiums, and operating premium-type liability reserves.
Pension Mathematics
This lecture covers basic pension mathematics. It deals with the search process for optimal fundraising methods that can be developed in the future and the existing fundraising methods suitable for appropriate asset management, focusing on corporate pensions and public pensions, and covers its related mathematical techniques.
Actuatial Risk Management
This lecture provides theories and techniques related to investment management and financial risk management that have been recently studied and applied. It deals with asset allocation strategies, asset pricing, risk modeling, and management techniques, focusing on practical case studies.
Principles of Insurance
This lecture covers he basic theory of insurance. It covers topics such as risk and the nature of insurance, types and functions of insurance, principles of insurance contracts, insurance company management, risk selection, insurance financial analysis, risk management, and insurance supervisory policy.
Seminar in Actuarial Science I
This lecture selects and covers an appropriate course among topics such as correction theory, the preparation method for life table and risk table, demographics, climate and weather derivatives, insurance business cost analysis, life insurance mathematics, pension mathematics, advanced theory related to non-life insurance, and risk management.