Study Program Doctorate
Department of Statistics - IPB University is considered as the pioneer institution in Indonesia to organize higher education in statistics and data science. Currently, this department is establishing Undergraduate, Master, and Doctoral Programs in Statistics and Data Science. The Department of Statistics has graduated qualified human resources that have been recognized both at the national and international levels. Many agencies, industries, and state institutions agree that graduates from the Department of Statistics can be relied upon and adapt quickly to meet the needs and challenges of work. A good learning process and high-quality student input have supported students to become the best in their fields, and the graduates can develop themselves in the areas of statistics and data science as well as various fields of its application.
Prof. Andi Hakim Nasoetion initiated the establishment of the Department of Statistics at 1968 through the Biometrics Section at the Faculty of Agriculture - IPB. Subsequently, it was officially established as the Department of Statistics and Computing in 1972 by holding an undergraduate education program. Since 1975 the Department of Statistics has also held a master program, while the regular doctoral program started in 1999. Currently, the department is supported by 29 lecturers of which 5 of them are professors. Master Program in Statistics and Data Science - IPB University has a capacity of 60 students per year.
Alumni of the master program have graduate expertise according to National Qualification Level 8 and are directed to fulfill capacities as data analysis managers (Head of Analytics, Data Processing Manager), senior researchers (Senior Researcher, Senior Research Executive, Senior Statistician), data scientists, and lecturers in statistics and data science.
To become a reference study program for developing excellent human resources in statistics, analytics, and data science who have high integrity and creativity, are adaptive to change and are globally competitive
Mission1. Building an academic atmosphere that supports educational and research activities in the fields of statistics and data science by following technological developments to answer future challenges, as well as producing graduates with integrity and creativity
2. Developing the human resource capacity of study program organizers who can keep up with the needs of the academic and applied fields.
3. Establishing cooperation and synergy with various parties to support the implementation of diverse education, research, and community service programs
Num | Course | Credit | Precondition | Semester | Course Category | |
---|---|---|---|---|---|---|
Code | Name | |||||
1 | STA1701 | Advanced Statistical Inference | 3(2-1) | - | 2 | Academic Core Courses |
2 | STA1751 | Advanced Data Analysis | 3(2-1) | - | 2 | Academic Core Courses |
3 | STA1791 | Special Topics in Statistics and Data Science | 3(2-1) | - | 1 | Academic Core Courses |
4 | PPS1792 | National Scientific Publication | 2(0-2) | - | 4 | Final Year Project |
5 | PPS1798 | Publication in Proceedings of International Seminar | 2(0-2) | - | 4 | Final Year Project |
6 | PPS1793 | National Scientific Publication | 3(0-3) | - | 5 | Final Year Project |
7 | STA1797 | Colloquium | 1(0-1) | - | 3 | Final Year Project |
8 | PPS1791 | Disertation Seminar | 1(0-1) | - | 6 | Final Year Project |
9 | STA179A | Written Qualification Exam | 2(0-2) | - | 2 | Final Year Project |
10 | STA179B | Oral Qualification Examination | 2(0-2) | - | 3 | Final Year Project |
11 | STA179C | Dissertation Proposal | 2(0-2) | - | 3 | Final Year Project |
12 | STA179D | Dissertation | 12(0-12) | - | 6 | Final Year Project |
13 | STA179E | Dissertation Examination | 3(0-3) | - | 6 | Final Year Project |
14 | STA1631 | Generalized Linear Models | 3(2-1) | - | 1 | Enrichment Program |
15 | PPS1704 | Philosophy of Science | 2(2-0) | - | 1 | PPKU/Common Core Courses |
16 | PPS1703 | English Courses for Doctoral | 3(3-0) | - | 1 | PPKU/Common Core Courses |
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Develop statistical science in collecting/generating, managing and presenting data for quantitative analysis in drawing valid conclusions.