Master of Science Program in Applied Statistics
Master of Science Program in Applied Statistics
The program concentrates on both theories and applications. Students may choose to major in statistics, actuarial science, risk management, business analytics and/or data science so they may apply the knowledge in their professions accordingly. This design is for the students to apply the knowledge to develop their professions, data-driven organizations and lifelong learning. The aim is to be adaptable to technological and environmental changes in the future.
Students may choose to study based on their needs and interests from three majors as follows:
- Statistics (STAT) focusing on becoming highly experienced in different types of statistics for data collection and data analysis.
- Actuarial Science and Risk Management (ACT) focusing on being highly experienced in analyzing data based on actuarial models for risk management and insurance.
- Citizen Data Sciences focusing on being highly experienced in statistics, and machine learning to apply in business analytics when making decisions.
Potential careers
Graduates can work as a teacher, lecturer, academic, researcher, data analyst, data scientist, actuary, business analytics consultant and so on.
| Plan A 2: Thesis | Plan B: Non-thesis | |
| Foundation courses | Non-credit | Non-credit |
| Core courses | 6 credits | 6 credits |
| Major courses | 24 credits | 24 credits |
| Elective courses (Minimum) | – | 9 credits |
| Independent study | – | 3 credits |
| Comprehensive exam | Exam | Exam |
| Oral exam | – | Exam |
| Thesis | 12 credits | – |
| (Passed thesis) | ||
| Not less than | 42 credits | 42 credits |
(1) Foundation courses
These are compulsory non-credit courses. Their grades are not calculated for grade average point purposes. The courses are divided into two groups as follows
Group 1 For students of all majors (regular programs)
ND 4000 Foundation for Graduate Studies
LC 4001 Reading Skills Development in English for Graduate Studies
LC 4002 Integrated English Language Skills Development
LC 4011* Remedial Reading Skills Development in English for Graduate Studies
LC 4012* Remedial Integrated English Language Skills Development
*In case of repeating courses
Group 2 For students of all majors (special programs: Saturday and Sunday classes)
AS 4001 Mathematics for Applied Statistics
AS 4002 English for Applied Statistics
Note
- Requirements and exemptions of foundation courses shall be as prescribed in a School/Institute’s announcement except those of English foundation courses offered by the Graduate School of Language and Communication, which shall be in accordance with the conditions of the English for Graduate Studies course.
- In case revision for the English for Graduate Studies course is required, English foundation courses of this program shall change according to the revised English for Graduate Studies course.
- AS 4002 English for Applied Statistics is a course offered to special program students subject to an announcement of the school.
(2) Core courses
These are for students of all majors to enroll in 2 courses (6 credits). The courses are as follows
AS 6001 Research Design and Inquiry Methods
AS 6002 Applied Predictive Analytics
(3) Major courses
These are for students to have specific expertise. Students in the Plan A2 and Plan B are to enroll in 8 courses (24 credits) as per their major requirements below
(3.1) Statistics Major
AS 7101 Theory of Probability and Applications
AS 7102 Statistical Inference
AS 7103 Statistical Graphics and Data Visualization
AS 7104 Sampling and Survey Data Analysis
AS 7105 Quantitative Forecasting
AS 7106 Applied Multivariate Data Analysis
AS 7107 Applied Categorical Data Analysis
AS 7108 Applied Longitudinal Data Analysis
(3.2) Actuarial Science and Risk Management Major
AS 7101 Theory of Probability and Applications
AS 7102 Statistical Inference
AS 7201 Enterprise Risk Management
AS 7202 Statistics for Risk Modeling
AS 7203 Financial Mathematics
AS 7204 Actuarial Mathematics
AS 7205 Credibility Theory and Loss Distributions
AS 7206 Credibility Theory and Loss Distributions
(3.3) Citizen Data Sciences Major
AS 7301 Strategic Intelligence
AS 7302 Applied Statistical Analysis
AS 7303 Accounting and Finance Data Sciences
AS 7304 Marketing Data Sciences
AS 7305 Operations Data Sciences
AS 7306 Operations Data Sciences
AS 7307 Risk Data Sciences
AS 7103 Statistical Graphics and Data Visualization
(4) Elective courses
These are divided into the courses coded AS 74XX comprising 2 groups and the course coded AS 80XX, which focuses on applied statistics. Plan B students are required to enroll in at least 8 credits.
Statistics and Data Analysis for Management
AS 7401 Quantitative Techniques for Decision Making
AS 7402 Data Wrangling and Cleansing
AS 7403 Applied Missing Data Analysis
AS 7404 Structural Equation Modeling
AS 7405 Multilevel Modeling
Statistics and Data Analysis for Management
AS 7406 Principles of Insurance
AS 7407 Long-Term Actuarial Mathematics
AS 7408 Survival Analysis
AS 7409 Accounting and Corporate Finance
AS 7410 Business Economics
AS 7411 Investment Analysis and Portfolio Management
AS 7412 Project Evaluation
Actuarial Science and Risk Management
AS 8001-8010 Selected Topics in Applied Statistics
Students may choose other elective courses, which are other core or elective courses at the graduate level offered by other programs of the School or other Schools. This is subject to advice of a supervisor and the availability of elective courses shall be according to the requirements of the School/Institute.
(5) Independent Study
AS 9000 Independent Study
(6) Thesis
AS 9004 Thesis
| -Expected Learning Outcomes (ELO)) | Generic skills | Specific skills | |
| ELO1 | Have morality in academics and science | ⁄ | |
| ELO 2 | Have knowledge and understanding of important principles and theories in the content of the field of applied statistics. Including the application of applied statistical knowledge. Let it be used for maximum benefit. | ⁄ | |
| ELO 3 | Able to apply knowledge of applied statistics, research, and information technology to be consistent with work processes. Solving problems in work Adjusting work processes In order to have the best performance results, you can research and learn by yourself. | ⁄ | |
| ELO 4 | Able to apply knowledge and understanding of related sciences to analyze and solve problems, think critically and systematically. | ⁄ | |
| ELO 5 | Be responsible for your own actions and take responsibility for your work in the group. | ⁄ | |
| ELO 6 | Have skills in using necessary tools | ⁄ | |
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