2025-2028 CURRICULUM OF MASTER PROGRAM IN STATISTICS

2025-2028 Curriculum of Master Program in Statistics

Vision

To become an educational institution for master program and developing statistics and data science international standard that contribute to science and technology, particularly in the fields of Computing, Business and Industry, Economics and Finance, Social and Population, and Environment and Health.

Mission

  1. The mission of the Master Program of Statistics is to contribute in the advancement of science and technology in the fields of statistics, data science, and its applications, in order to achieve societal welfare through activities in education, research, community service, and management based on information and communication technology.
  2. The mission of the Master Program of Statistics in the field of Education is to:
    • Provide graduate education based on information and communication technology, with a curriculum, faculty, and teaching methods that meet international standards, in order to produce graduates of international quality in the fields of Statistics and Data Science, along with its applications;
    • Produce graduates who are devout and pious to God Almighty and possess noble morals and character;
    • Equip graduates with entrepreneurial knowledge based on technology
  3. The mission of the Master Program of Statistics in the field of research is to actively contribute to science and technology in the field of computing-based Statistics and Data Science and its application through high quality research activities of international standards in the fields of Industry, Business, Economy, Social, Health, and Environment.
  4. The mission of the Master Program of Statistic in the area of community service is to utilize its resources to actively participate in solving problems faced by the society, industry, and government by prioritizing information and communication technology facilities.
  5. The mission of the Master Program of Statistic in management:
    • The management of the Study Program is carried out by paying attention to the principles of good governance supported by information and communication technology;
    • Creating a conducive environment and providing full support to Students, Lecturers, Education Staff to develop themselves and make maximum contributions to society, industry, science and technology; and
    • Establishing networks to synergize with other universities, industries, society, and the government in conducting educational, research, and community service activities.

Program Educational Objectives

Program Educational Objectives (PEO) reflects the achievements of graduates of the study program. The PEO of the Master Program of Statistics is to produce quality Masters in Statistics so that they can have a career as lecturers, researchers, and practitioners in the field of Statistics and Data Science with the following characteristics:

    1. To produce graduates with a Master’s degree in Statistics who are noble, have good personality and independence, possess professional skills and ethics, demonstrate high integrity and responsibility, and have the ability to develop themselves and compete at the international level.
    2. To produce high-quality Master’s degree graduates in Statistics who can pursue careers as lecturers, researchers, consultants, and practitioners in the field of Statistics and Data Science based on computation, and who are capable of using and developing knowledge, skills, and competencies professionally to solve problems in their profession in an interdisciplinary manner within the fields of Industry, Business, Economics, Social Sciences, Health, and Environment.
    3. To produce Master’s degree graduates in Statistics who have the character to develop themselves through lifelong learning, including research, training, professional activities, and advanced studies at the Doctoral level both domestically and internationally.

Programme Learning Outcome (PLO)

PLO-1: Able to demonstrate attitudes and characters that reflect: being pious to God Almighty, having ethics and integrity, virtuous character, sensitive and concern with social and environmental issues, respecting cultural differences and pluralism, upholding law enforcement, prioritizing the interests of the nation and the wider community, through creativity and innovation, excellence, strong leadership, synergy, and other potentials to achieve maximum results.
PLO-2: Able to develop and solve science and technology problems in their field through research with an inter or multidisciplinary approach to produce innovative and tested works in the form of theses and papers that have been accepted in accredited national journals or accepted at reputable international seminars.
PLO-3: Able to manage their own learning and develop themselves as personal lifelong learners to compete at national and international levels, in order to make a real contribution to solving problems by implementing information and communication technology and paying attention to the principle of sustainability.
PLO-4: Able to analyze and integrate Statistical Theory in formulating innovative statistical methods to address both theoretical and real-world problems.
PLO-5: Able to design, implement, and evaluate methodologies for collecting structured and unstructured data, as well as to modify sampling and data-collection methods.
PLO-6: Able to integrate modern computational tools to develop efficient statistical solutions, while evaluating the reliability and accuracy of computational results.
PLO-7: Able to analyze and evaluate statistical computing techniques to solve complex, data-driven statistical problems.
PLO-8: Able to analyze and evaluate statistical methods to formulate solutions for theoretical and real-world problems through a multidisciplinary approach.
PLO-9: Able to analyze and evaluate innovative computational or analytical statistical methods to address real-world problems in business, industry, economics, finance, social and sustainable development, environment, and health, as well as to assess their impact on decision-making.

Regular Track

Distribution of Courses per Semester

SEMESTER I
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255101 Probability Theory 3 link link
2 SS255102 Sampling Methods 3 link link
3 SS255103 Linear Model 3 link link
4 UG255101 English 2 link link
5 SS255— Elective Course 1 3 link link
Total Credit 14

 

SEMESTER II
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255201 Statistical Inference 3 link link
2 SS255202 Multivariate Analysis 3 link link
3 SS255203 Intensive Computational Statistics 3 link link
4 SS255203 Advanced Data Analysis 3 link link
Total Credit 12

 

SEMESTER III
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255301 Thesis Research Methodology 2 link link
2 SS255302 Thesis Proposal 2 link link
3 SS255— Elective Course 2 3 link link
Total Credit 7

 

SEMESTER IV
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255401 Thesis 5 link link
Total Credit 5

Research Track

Distribution of Courses per Semester

SEMESTER I
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255301 Thesis Research Methodology 2 link link
2 SS255172 Research Thesis Proposal 3 link link
4 UG255101 English 2 link link
5 SS255— Elective Course 1 3 link link
Total Credit 10

 

SEMESTER II
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255271 Thesis I 5 link link
2 SS255— Elective Course 2 3 link link
Total Credit 8

 

SEMESTER III
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255371 Thesis II 6 link link
2 SS255372 Research Publication I 6 link link
Total Credit 12

 

SEMESTER IV
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255471 Research Publication II 8 link link
Total Credit 8

List of Elective Course

List of Elective Course
No. Course Code Course Name Sks Document
Syllabus Handbook
1 SS255111 Bayesian Analysis 3 link link
2 SS255212 Advanced Simulation Techniques 3 link link
3 SS255213 Advanced Stochastic Process 3 link link
4 SS255314 Enterprise Data Analytics 3 link link
5 SS255315 Advanced Data Organization 3 link link
6 SS255091 Computational Statistics (Matriculation) 3 link link
7 SS255092 Data Analysis (Matriculation) 3 link link
8 SS255321 Process Control Analysis 3 link link
9 SS255222 Intelligent Quality Design 3 link link
10 SS255223 Reliability Analysis 3 link link
11 SS255324 Statistical Consulting 3 link link
12 SS255093 Statistical Analysis (Matriculation) 3 link link
13 SS255095 Statistical Analysis 3 link link
14 SS255331 Econometrics 3 link link
15 SS255332 Financial Statistics 3 link link
16 SS255233 Time Series Analysis 3 link link
17 SS255234 Advanced Statistical Machine Learning 3 link link
18 SS255335 Applied Statistics Capita Selecta 3 link link
19 SS255094 Mathematical Statistics (Matriculation) 3 link link
20 SS255141 Official Statistics Analysis 3 link link
21 SS255242 Advanced Nonparametric Regression 3 link link
22 SS255243 Marketing Research Methods 3 link link
23 SS255244 Population Analysis 3 link link
24 SS255351 Qualitative Data Analysis 3 link link
25 SS255352 Survival Analysis 3 link link
26 SS255253 Spatial Statistics 3 link link
27 SS255254 Meta Analysis 3 link link
28 SS255355 Advanced Experimental Design 3 link link

Module Handbook

Regular Track Distribution of Course

SEMESTER: I
No. Course Code Course Name Credit
1 SS255101 Probability Theory 3
2 SS255102 Sampling Methods 3
3 SS255103 Linear Model 3
4 UG255101 English 2
5 SS255— Elective Course 1 3
Total Credit 14

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS255201 Statistical Inference 3
2 SS255202 Multivariate Analysis 3
3 SS255203 Intensive Computational Statistics 3
4 SS255204 Advanced Data Analysis 3
Total Credit 12

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS255301 Thesis Research Methodology 2
2 SS255302 Thesis Proposal 2
3 SS255— Elective Course 2 3
Total Credit 7

 

SEMESTER: IV
No. Course Code Course Name Credit
1 SS255401 Thesis 5
Total Credit 5

Research Track Distribution of Course

SEMESTER: I
No. Course Code Course Name Credit
1 SS255301 Thesis Research Methodology 2
2 SS255172 Research Thesis Proposal 3
3 UG255101 English 2
4 SS255— Elective Course 1 3
Total Credit 10

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS255271 Thesis I 5
2 SS255— Elective Course 2 3
Total Credit 8

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS255371 Thesis II 6
2 SS255372 Research Publication I 6
Total Credit 12

 

SEMESTER: IV
No. Course Code Course Name Credit
1 SS255471 Research Publication II 8
Total Credit 8

List of Elective Course

List of Elective Course
No Course Code Course Name Credit Lab. Name
1 SS255111 Bayesian Analysis 3 SCDS
2 SS255212 Advanced Simulation Techniques 3 SCDS
3 SS255213 Advanced Stochastic Process 3 SCDS
4 SS255314 Enterprise Data Analytics 3 SCDS
5 SS255315 Enterprise Data Analytics 3 SCDS
6 SS255091 Computational Statistics (Matriculation) 3 SCDS
7 SS255092 Data Analysis (Matriculation) 3 SCDS
8 SS255321 Process Control Analysis 3 BIDA
9 SS255222 Intelligent Quality Design 3 BIDA
10 SS255223 Reliability Analysis 3 BIDA
11 SS255324 Statistical Consulting 3 BIDA
12 SS255093 Statistical Analysis (Matriculation) 3 BIDA
13 SS255095 Statistical Analysis 3 BIDA
14 SS255331 Econometrics 3 BIDA
15 SS255332 Financial Statistics 3 EFDA
16 SS255233 Time Series Analysis 3 EFDA
17 SS255234 Advanced Statistical Machine Learning 3 EFDA
18 SS255335 Applied Statistics Capita Selecta 3 EFDA
19 SS255094 Mathematical Statistics (Matriculation) 3 EFDA
20 SS255141 Official Statistics Analysis 3 OSSDA
21 SS255242 Advanced Nonparametric Regression 3 OSSDA
22 SS255243 Marketing Research Methods 3 OSSDA
23 SS255244 Population Analysis 3 OSSDA
24 SS255351 Qualitative Data Analysis 3 OSSDA
25 SS255352 Survival Analysis 3 EHSDS
26 SS255253 Spatial Statistics 3 EHSDS
27 SS255254 Meta Analysis 3 EHSDS
28 SS255355 Advanced Experimental Design 3 EHSDS

Thesis Writing Guidelines

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