COLLEGE OF MANAGEMENT
Department of Statistics
Degrees Offered:B.A., M.B.A.
TO Webpage:
Chair:Tsai, Tzong-ru
The Department
The forerunner of the Department of Statistics was the Statistics Section in the Department of Accounting and Statistics founded in 1963. The Department of Statistics was organized as an independent department in 1973. The master's program was established in 1997. Since 1963, over 7,000 Bachelor's degrees and Master's degrees have been granted.
The Department offers broad undergraduate and graduate programs to meet the diverse needs of students at different levels. Both programs give students sufficient flexibility to pursue their special interests and time to take courses in other departments. At the undergraduate level, there are several introductory courses which lead to many more advanced courses that are designed to provide students with understanding of the concepts of statistical inference and familiarity with the methods of applied statistical analysis. The Department's master program stresses a balance between statistical theory and practical applications, preparing students for careers in industry, business, government, medical research, and academia. Both undergraduate and graduate programs cultivate students' abilities to do data analysis of real world problems in diverse areas.
The Department mainly emphasizes the practice of sample survey, marketing analysis, industrial engineering, biological sciences, and many other areas. To accomplish the Triple-Objective of the University and multimedia-aided instruction, all faculty members are encouraged to make multimedia-aided teaching materials for the required courses. By combining the interest and expertise of the faculty with the campus information network, we encourage faculty and graduate students to engage in cooperative research with people in other areas. To adjust to the age of the knowledge economy, promote competitive capability, meet the demands of industry, offer opportunities for in-service people, and train students to be statistical specialists both in theory and practice, the Department, in collaboration with the Graduate Institute of Management Sciences, offers a Ph.D. degree in Management Sciences with emphasis on Statistics.
Faculty
Professors
Chang, Chun-tao ; Lin, Jyh-jiuan ; Lin, Kuang-nan;
Tsai, Tzong-ru ; Wu, Chin-chuan ; Wu, Shu-fei ;
Wu, Shuo-jye
Associate Professors
Chen, Ching-hsiang ; Deng, Wen-shuenn ; Lee, Hsiu-mei ;
Wen, Bor-shyh
Assistant Professors
Chen , Li-ching ; Chen, Man-hua ; Chen, Yi-ju ;
Chen, Yi-ju (Vivian) ; Li, Pai-ling
Lecturers
Wang, Wen-yen ; Yang, Wen
Degree Requirements
The Department of Statistics offers both undergraduate and graduate programs.
- Requirements for a degree of B.A. in Statistics:
Completion of 139 credits of courses, including 102 credits of required courses and 20 credits of elective statistics courses.
- Requirements for a degree of M.B.A. in Statistics:
A master's degree requires a minimum of 36 graduate credits including 9 credits of required courses, 4 credits of Topics in Applied Statistics and 4 credits of Seminar. At least 30 credits must be completed within the Department. Student are required to complete a thesis under the supervision of a faculty member of the Department, submit a thesis, and pass an oral examination on the thesis.
Course Descriptions
Undergraduate Courses
B0106 Actuarial Analysis (0/3) This course covers the theory of interest, concepts of certain annuities, measurement of mortality and life table, life annuities, life insurance, net annual premium, net level premium reserves, pricing for casualty insurance, statistical base, overall average pure premium and/or loss ratio, construction of loading and gross premium, risk classification, and ration plan.
B0109 Insurance (3/0) Topics include: what insurance is all about: risk management and insurance, insurance and the law, insurance contracts policy analysis, limitation of amount of recovery, and loss-adjustment provisions.
B0263 Money and Banking (2/2) This course deals with the nature and functions of money and finance, commercial banking, central banking, monetary theory, and international monetary relations.
B0302 Economics (3/3) This course discusses two main topics: individual economy includes price and theory of supply and demand, analysis of acts consumers, theory of production, structure of cost, structure of market, and supply and demand of production factors; and collective economy as the study of national income, determining rules for equalization of income standard.
B0456 Security Investment Analysis (0/2) This course focuses on equities analysis of investment. Students can learn how to invest securities in stock markets. Moreover, the course emphasizes reasonable prices of companies, including fundamental analysis, technical analysis, when and how to buy and sell by investors, and how to set up investment framework of top-to-down.
E1034 Introduction to Information Science (2/2) Topics of this course cover: 1. Introduction to information society; 2. Networking operations and applications; 3. Word processing; 4. Hardware of computers; 5. Software of computers; 6. Applications of computer; 7. Computer programming.
M0115 Multivariate Analysis (0/3) This course covers review of matrix theory, univariate and multivariate normal distributions. Inference about multivariate means including Hotelling's T squared. Inference about covariance structure including principal components, factor analysis, and canonical correlation. Classification techniques including discriminant and cluster analysis.
M0153 Operations Research (0/3) This course includes basic techniques for modeling and optimizing deterministic systems and stochastic models with emphasis on linear programming, integer programming, queuing theory, and inventory. Applications to production, logistics, and service systems are also covered.
M0184 Applied Computer Programmings in Statistics (2/2) This course discusses a basic and concise introduction of the programming language R and introduces some programming skills with the language regarding statistics in data manipulation, calculation and graphical display.
M0191 Survey Sampling (3/0) This course offers an introduction to the design of sample surveys and the analysis of survey data, the course emphasizes practical applications of survey methodology. Topics include sources of errors in surveys, questionnaire construction, simple random, stratified, systematic and cluster sampling.
M0202 Quality Control (2/2) This course offers an introduction to statistically based quality improvement methods useful in industrial settings, inspection data for quality control, sampling plans for acceptance inspection, and charts for process control.
M0203 Case Studies in Government Statistics (2/2) This course covers an introduction to the organization and major responsibilities of Government Statistics Affairs, and focuses on the training of case studies. This course also emphasizes the needs of sitting for Civil Service Examination.
M0264 Time Series (0/3) This course covers autocorrelation and elements of spectral analysis, auto-regressive and moving average models, identification and fitting, forecasting, and seasonal adjustment.
M0339 Accounting I (3/3) This course focuses on the accounting concept, the accounting model, and the financial statements. The course also discusses the accounting of single proprietorship, partnership, and corporation.
M0344 Data Processing (2/2) This course aims to introduce students to use computer to administrate, process and manage mass and complex data.
M0364 Computer Applications in Statistics (2/2) This course covers organization and application of computers and statistical packages to data processing. Other topics also include data handling in terms of coding, preparation, acquisition, file organization and retrieval, screening and reduction, summarization and tabulation, statistical analysis, and survey of available packages and applications.
M0404 Management Mathematics (3/3) This course introduces several mathematical models and methods for various real world situations that may be encountered in the applications of management sciences. Emphasis of the course is on its applications.
M0405 Management (3/0) The course offers students not only theoretical frameworks that guide managerial activities but also illustrations and examples of how and when those theories do and do not work in both small and large businesses as well as in nonprofit organizations.
M0481 Categorical Data Analysis (3/0) This course covers methods of analyzing multidimensional contingency tables with an emphasis on practical applications. Topics cover the use of computing packages for analysis of such data, model selection, testing goodness of fit, and estimation of parameters.
M0517 Statistics (3/3) This course covers graphical and numerical descriptive measures, probability, random variables, expectations and variances, sampling distributions, central limit theorem, confidence intervals, hypothesis testing, chi-square tests, analysis of variance, regression analysis and nonparametric statistics.
M1043 Survival Data Analysis (0/3) This course provides an overview of survival data analysis, including introduction of the lifetime variable, censored data, parametric and nonparametric inference.
M1190 Special Topic in Applied Statistics (2/2) This course helps students to build up the ability to propose a project, collect the related data and make decision.
M1302 Special Topics in Statistical Application and Exploration (0/2) This lecture course is to provide an overview of the field for students who will continue to study cases in applied statistics.
M1601 Seminar on Statistics (2/2) This course includes special topics in probability theory and mathematical statistics designed to meet the needs and interests of individual students.
M1744 Applied Statistical Methods (2/2) This long-distance learning course targets at audience who want to solve daily-life problems efficiently with software EXCEL. Statistical techniques of converting data into information are introduced through dynamic and graphic presentations. Statistical background is helpful but not necessarily required in this course.
M1831 Investment Theory and Market of Security (3/0) This course focuses on investing equities in stock markets, fixed-income, mutual funds, options and futures. Theories and their applications, and a connection between the course and getting finance certificates will be introduced in class.
S0061 Reliability Analysis (3/0) This course covers analysis of failure data, estimates of hazard rates and failure time distributions for the reliability of components and/or systems. Additional topics may be included at the discretion of the instructor, if time permits.
S0075 Biostatistics (2/2) This course provides a comprehensive introduction of basic statistical approaches and focuses on biomedical applications. Students can learn how to deal with biomedical problems via statistical methods through analyzing real examples.
S0191 Regression Analysis (3/0) This course is an introduction to regression with emphasis on practical applications, including simple linear regression and multiple linear regression models, inference about model parameters and predictions, diagnostic and remedial measures about the model, independent variable selection, and multicolinearity.
S0210 Advanced Calculus (2/2) This course covers fundamental notions of limits, continuity, differentiation, and integration, for functions of one or more variables, convergence of infinite series, and improper integrals. Prerequisite: Calculus.
S0295 Nonparametric Statistics (3/0) This course is an introduction to nonparametric statistics, including one or two sample testing and estimation methods, one or two way layout models, sign test, signed rank tests, rank tests, Mann Whitney Wilcoxon procedures, Kolmogorov Smirnov tests, and discussion and comparison with parametric methods.
S0325 Calculus (3/3) This course covers limits, differentiation and integration of functions of one variable, infinite series, functions of several variables, partial derivatives, and multiple integral.
S0408 Design of Experiments (0/3) This course offers an introduction to the basic principles of experimental design. Topics include analysis of variance for experiments with a single factor, randomized blocks and Latin square designs, multiple comparison of treatment means, factorial and fractional factorial designs, and nested designs.
S0439 Linear Algebra (2/2) Topics of this course include: matrix algebra, linear systems of equations, vector spaces, subspaces, linear dependence, rank of matrices, determinants, linear transformations, eigenvalues and eigenvectors, diagonalization, inner products and orthogonal vectors.
S0440 Linear Programming (3/0) This course is an introduction to techniques for modeling and optimizing deterministic systems, computer solution of optimization problems, applications to production, logistics, and service systems.
S0450 Introduction to Probability Theory (3/3) This course offers an introduction to the theory of probability, conditional probability, independence, Bayes rule, random variables and their distributions, and moment generating functions. Multivariate probability distributions, covariance, distributions of functions of random variables, sampling distributions, limiting theorems and order statistics are covered. Prerequisite: Calculus.
S0582 Mathematical Statistics (3/3) Topics of this course include: sufficiency, completeness, unbiased estimation, maximum likelihood estimation, Bayes estimation, confidence intervals, tests of hypotheses, Neyman-Pearson fundamental lemma, uniformly most powerful and likelihood ratio tests. Prerequisite: Introduction to Probability Theory.
Master's Program
B0486 Seminar on Financial Management (3/0) This course provides a comprehensive description of value-at-risk, a new benchmark to measure financial market risks. Recent VaR estimation methods' development is stressed mainly in this course.
M0189 Sampling Theory (0/3) This course covers concepts of sampling survey, major sampling designs and its estimation procedures, and evaluation of precision of a sampling design.
M0303 Statistical Theory (3/3) The purpose of this course is to build theoretical statistics from the first principles of probability theory, logical development, proofs, ideas, themes, etc., evolving through statistical arguments.
M0481 Categorical Data Analysis (0/3) This course is concerned with statistical methods for describing and analyzing categorical data. The main topics are the basic concepts of categorical data, chi-square test, loglinear model, and logistic model.
M0798 Statistical Consulting (3/0) This course includes topics such as consulting experience in data analysis and applied statistics. Students are expected to learn communication techniques and study cases from various fields of real-world data.
M0880 Applied Linear Model (3/0) This course provides an exposition of the theory of linear models including practical aspects of residuals and data analysis.
M0883 Statistical Computing (3/0) This course emphasizes statistical computing and simulation, including Monte Carlo simulation methods, Validation techniques, statistical analysis of simulated data, bootstrap resampling, and etc.
M1014 Statistical Quality Control (0/3) The purpose in learning statistical quality control is to give students a strategy for effective use of statistics in the area of process control. Moreover, a paper study is conducted in this course.
M1043 Survival Data Analysis (3/0) This course provides an overview of survival data analysis, including an introduction of the lifetime variable, censored data, parametric and nonparametric inference. Some advanced topics in biomedical applications will be also discussed.
M1883 Statistical Methods in Clinical Trials (0/3) This is a survey course with a focus on the concepts of statistical design and analysis in biomedical research, with special emphasis on clinical trials. This course will be devoted mostly to statistical principles and methods in Clinical Trials research but we will first give a very brief introduction to Epidemiology in the beginning. SAS for Windows statistical software will be used throughout the course for data analysis.
S0408 Design of Experiments (3/0) This course is concerned with the learning of the design and analysis of experiment in engineering applications. The statistical software package Minitab is used to conduct the data analyses of examples in the textbook so that students can follow the techniques of DOE easily.
S0594 Nonparametric Regression (0/3) Nonparametric regression is a smoothing method for recovering the unknown regression function from noisy data, without pre-specifying the functional form of the regression function. The kernel smoothing (or local polynomials) method, which is very simple and useful among other several nonparametric alternatives, will be introduced in greater detail.
T0102 Seminar (2/2) This course provides discussions in the methods and theories of statistics and studies in some reputable statistical papers.
Ph.D. Program
M1523 Advanced Statistical Inference (3/3) Topics of this course include sufficiency and completeness, unbiased and equivariant estimators, interval estimation, Neyman-Pearson, UMP, UMPU and LR tests, asymptotic theory for estimators and tests, and other topics in modern inference.
M1717 Special Topics in Statistical Quality Control (3/0) The course is concerned with how to use the modern statistical methods to develop new techniques for quality control and improvement. The objective is to give the students a training of working quality control papers.