2023-2028 CURRICULUM OF MASTER PROGRAM IN STATISTICS

2023-2028 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:

  • 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.
  • 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.
  • 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 apply Statistical Theory to Statistical Methods
PLO-5: Able to design, implement, and evaluate data collection with appropriate methodology
PLO-6: Able to use modern computing devices to solve statistical problems
PLO-7: Able to apply and evaluate computational techniques to solve statistical problems
PLO-8: Able to apply statistical methods appropriately and evaluate them to analyze theoretical and real problems
PLO-9: Able to apply Computing-based Business, Industrial, Financial Economics, Social-Population, Environmental, or Health Statistics methods to real problems

Distribution of Courses per Semester

SEMESTER: I
No. Course Code Course Name Credit
1 SS235101 Probability Theory 3
2 SS235102 Sampling Methods 3
3 SS235103 Linear Model 3
4 SS235— Elective Course I 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS235201 Statistical Inference 3
2 SS235202 Multivariate Analysis 3
3 SS235203 Intensive Computational Statistics 3
4 SS235— Elective Course II 3
Total credit 12

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS235301 Advanced Data Analysis 3
2 SS235302 Thesis Proposal 3
Total credit 6

 

SEMESTER: IV
No. Course Code Course Name Credit
1 SS235401 Thesis 6
Total credit 6

Distribution of Courses per Semester (Research Track)

SEMESTER: I
No. CourceCode Course Name Credit
1 SS235171 Research Methods 3
2 SS235171 Thesis Research Proposal 3
3 SS235— Elective Course I 3
4 SS235— Elective Course II 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS235271 Thesis I 4
2 SS235272 Research Publication I 6
Total credit 10

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS235371 Thesis II 6
Total credit 6

 

SEMESTER: IV
No. Course Code Course name Credit
1 SS235471 Research Publication II 8
Total credit 8

List of Elective Course

No Course Code Elective Course Name Credit Lab. Name
1 SS235111 Bayesian Analysis 3 SCDS
2 SS235112 Advanced Simulation Technique 3 SCDS
3 SS235113 Advanced Stochastic Process 3 SCDS
4 SS235314 Enterprise Data Analytics 3 SCDS
5 SS235315 Advanced Data Organization 3 SCDS
6 SS235091 Computational Statistics (Matriculation) 3 SCDS
7 SS235092 Data Analysis (Matriculation) 3 SCDS
8 SS235321 Process Control Analysis 3 BIS
9 SS235322 Quality Design Analysis 3 BIS
10 SS235323 Reliability Analysis 3 BIS
11 SS235324 Consulting Statistics 3 BIS
12 SS235325 Research Methodology and Colloqium 3 BIS
13 SS235093 Statistical Analysis (Matriculation) 3 BIS
14 SS235095 Statistical Analysis 3 BIS
15 SS235331 Econometrics 3 EFDA
16 SS235332 Financial Statistics 3 EFDA
17 SS235333 Time Series Analysis 3 EFDA
18 SS235334 Advanced Statistical Machine Learning 3 EFDA
19 SS235335 Applied Statistics Capita Selecta 3 EFDA
20 SS235094 Mathematical Statistics (Matriculation) 3 EFDA
21 SS235141 Official Statistics Analysis 3 SPS
22 SS235242 Advanced Nonparametric Regression 3 SPS
23 SS235243 Marketing Research Methods 3 SPS
24 SS235244 Population Analysis 3 SPS
25 SS235351 Qualitative Data Analysis 3 SEH
26 SS235352 Survival Analysis 3 SEH
27 SS235353 Spatial Statistics 3 SEH
28 SS235354 Meta Analysis 3 SEH
29 SS235355 Advanced Experimental Design 3 SEH

Distribution of Courses per Semester

SEMESTER: I
No. Course Code Course Name Credit
1 SS235101 Probability Theory 3
2 SS235102 Sampling Methods 3
3 SS235103 Linear Model 3
4 SS235— Elective Course I 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS235201 Statistical Inference 3
2 SS235202 Multivariate Analysis 3
3 SS235203 Intensive Computational Statistics 3
4 SS235— Elective Course II 3
Total credit 12

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS235301 Advanced Data Analysis 3
2 SS235302 Thesis Proposal 3
Total credit 6

 

SEMESTER: IV
No. Course Code Course Name Credit
1 SS235401 Thesis 6
Total credit 6

Distribution of Courses per Semester (Research Track)

SEMESTER: I
No. CourceCode Course Name Credit
1 SS235171 Research Methods 3
2 SS235171 Thesis Research Proposal 3
3 SS235— Elective Course I 3
4 SS235— Elective Course II 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 SS235271 Thesis I 4
2 SS235272 Research Publication I 6
Total credit 10

 

SEMESTER: III
No. Course Code Course Name Credit
1 SS235371 Thesis II 6
Total credit 6

 

SEMESTER: IV
No. Course Code Course name Credit
1 SS235471 Research Publication II 8
Total credit 8

List of Elective Course

No Course Code Elective Course Name Credit Lab. Name
1 SS235111 Bayesian Analysis 3 SCDS
2 SS235112 Advanced Simulation Technique 3 SCDS
3 SS235113 Advanced Stochastic Process 3 SCDS
4 SS235314 Enterprise Data Analytics 3 SCDS
5 SS235315 Advanced Data Organization 3 SCDS
6 SS235091 Computational Statistics (Matriculation) 3 SCDS
7 SS235092 Data Analysis (Matriculation) 3 SCDS
8 SS235321 Process Control Analysis 3 BIS
9 SS235322 Quality Design Analysis 3 BIS
10 SS235323 Reliability Analysis 3 BIS
11 SS235324 Consulting Statistics 3 BIS
12 SS235325 Research Methodology and Colloqium 3 BIS
13 SS235093 Statistical Analysis (Matriculation) 3 BIS
14 SS235095 Statistical Analysis 3 BIS
15 SS235331 Econometrics 3 EFDA
16 SS235332 Financial Statistics 3 EFDA
17 SS235333 Time Series Analysis 3 EFDA
18 SS235334 Advanced Statistical Machine Learning 3 EFDA
19 SS235335 Applied Statistics Capita Selecta 3 EFDA
20 SS235094 Mathematical Statistics (Matriculation) 3 EFDA
21 SS235141 Official Statistics Analysis 3 SPS
22 SS235242 Advanced Nonparametric Regression 3 SPS
23 SS235243 Marketing Research Methods 3 SPS
24 SS235244 Population Analysis 3 SPS
25 SS235351 Qualitative Data Analysis 3 SEH
26 SS235352 Survival Analysis 3 SEH
27 SS235353 Spatial Statistics 3 SEH
28 SS235354 Meta Analysis 3 SEH
29 SS235355 Advanced Experimental Design 3 SEH

Thesis Writing Guidelines

Registration