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Statistics

Applied Bachelor's Degree Program

Learn more about various concentrations, explore the Curriculum adjust your Course Schedule to fit your time, know the required Tuition Fees, and understand the expected learning outcomes All the information you need to start your academic journey is here.

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Concentration

The following is a list of specializations contained in Applied Bachelor's Degree Program in Statistics

Probability Modeling

Probability Modeling

The Probability Modeling specialization in the Applied Bachelor’s Degree Program in Statistics is designed to equip students with in-depth knowledge and practical skills in understanding, formulating, and modeling complex random phenomena. This specialization emphasizes the application of probability theory and probability distributions in identifying patterns, forecasting events, and supporting risk-based decision-making across various fields. Through a comprehensive curriculum, students will study fundamental concepts such as advanced probability theory, multivariate distributions, stochastic processes, Monte Carlo simulation, and applied probability modeling techniques for industry and business. Learning is focused on mastering quantitative methods and relevant statistical programming, enabling graduates to conduct risk analysis, optimize processes, and provide accurate probabilistic recommendations. The excellence of this specialization is supported by intensive practicums, real case studies, and collaborations with industry, ensuring students develop the ability to interpret analytical results and communicate findings effectively. Thus, the Probability Modeling specialization plays a vital role in producing applied statistics experts who are adaptive, ethical, and competitive in the era of Industry 4.0 and in data-driven decision-making ecosystems.
Statistical Computing

Statistical Computing

The Statistical Computing specialization in the Applied Bachelor’s Degree Program in Statistics aims to produce graduates who excel in applying modern computational techniques for data analysis. This specialization is specifically designed to address the challenges of the big data era and digital transformation, equipping students with the ability to process, analyze, and visualize large-scale data efficiently. Students in this specialization will learn various statistical algorithms, numerical methods, and statistical programming using state-of-the-art languages and software such as R, Python, SQL, and interactive visualization tools. The scope of study includes inferential computing, statistical simulation, applied machine learning, spatial and temporal data analysis, and the application of cloud computing for big data analytics. This specialization also emphasizes hands-on practice and real-world case studies from industry, government, and research sectors, allowing students to develop computational problem-solving skills and adapt quickly to technological advances. In addition, soft skills such as analytical thinking, problem-solving, and effective communication of results are fostered to ensure graduates are prepared to thrive in a highly dynamic job market. With an adaptive curriculum and the support of experienced faculty, the Statistical Computing specialization stands out as one of the strengths of the Applied Bachelor’s Degree Program in Statistics, producing applied statistics professionals who are innovative, reliable, and capable of delivering data-driven solutions across diverse sectors of development.
Demographic Statistics

Demographic Statistics

The Demographic Statistics specialization in the Applied Bachelor’s Degree Program in Statistics is designed to provide students with analytical and technical competencies in understanding population dynamics through a statistical approach. This specialization focuses on the collection, processing, analysis, and interpretation of demographic data to support evidence-based development planning. Students will learn various demographic concepts and indicators such as fertility, mortality, migration, age structure, population projections, as well as statistical techniques used in population studies. This learning is supported by the application of statistical and demographic software, social survey analysis, and the interpretation of census and large-scale survey data such as IDHS, Intercensal Survey, and National Socioeconomic Survey. The strength of this specialization lies in integrating demographic theory with hands-on practice through real case studies in population, public health, labor, and housing. With this approach, graduates are expected to produce accurate and relevant demographic statistics that can be utilized to support policies of both government and private institutions. The Demographic Statistics specialization serves as one of the key pillars of the Applied Bachelor’s Degree Program in Statistics, committed to producing applied statistics professionals with social sensitivity, strong technical capabilities, and readiness to contribute to solving strategic challenges in human development in Indonesia.
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Curriculum

The following is a complete list of courses that will be taken in each semester.

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Course Schedule

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Tuition Fee

Here are the study fees Applied Bachelor's Degree Program In Statistics
Applied Bachelor's SNBP & SNBT Pathway
UKT Group I IDR 500,000
UKT Group II IDR 1,000,000
UKT Group III IDR 2,400,000
UKT Group IV IDR 3,100,000
UKT Group V IDR 4,400,000
UKT Group VI IDR 5,700,000
UKT Group VII IDR 7,000,000
UKT Group VIII IDR 8,800,000
Applied Bachelor's Single Tuition Fee
Single Tuition Fee 1 IDR 500,000
Single Tuition Fee 2 IDR 1,000,000
Single Tuition Fee 3 IDR 2,400,000
Single Tuition Fee 4 IDR 3,100,000
Single Tuition Fee 5 IDR 4,400,000
Single Tuition Fee 6 IDR 5,700,000
Single Tuition Fee 7 IDR 7,000,000
Single Tuition Fee 8 IDR 8,800,000
UKT is paid every semester during the study period
Applied Bachelor's Institutional Development Fee (Independent Program Only)
IDR 14,000,000 One-Time Payment
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Learning Outcomes

Learning Outcomes
1 Capable of applying professionalism, integrity, honesty, and responsibility in keeping up with developments in statistical science.
2 Capable of identifying industrial and social problems following the principles of statistics.
3 Capable of explaining industrial and social issues using fundamental statistical knowledge, supported by strong literacy and communication skills.
4 Capable of formulating industrial and social problems to be solved based on scientific principles, procedures, and ethics systematically through case studies or projects, grounded on information and data analysis.
5 Capable of applying statistical methods, programming techniques, and statistical computing in solving industrial and social problems.
6 Capable of providing innovative solutions to industrial and social problems based on statistical science.
7 Capable of analyzing data related to industrial and social problems in terms of interpretation, visualization, and forecasting using big data.
8 Capable of integrating statistical knowledge to easily adapt and collaborate in the workplace, while demonstrating high-quality, professional, and effective performance.
9 Capable of evaluating and innovating by applying new methods in statistics and computing to address current and dynamic issues, providing appropriate solutions, particularly for industrial and social problems, based on the competitive excellence of USU TALENTA.