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MKU6201

Islamic Education

The subject of Islamic Education is compulsory for every Muslim student in all study programs at Universitas Negeri Yogyakarta. This course is designed with the intention of strengthening students' faith and piety to Allah SWT, and have noble character and broaden the horizons of their religious life, to form Muslim students who have a noble character, think philosophically, are rational and dynamic, and have broad views, taking into account the demands to establish harmony among human beings both within one religion and with people of other religions

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MKU6202

Catholic Education

The Catholic Religious Education course is mandatory for every Catholic student in all study programs, weighing 3 credit hours. This course is designed to strengthen faith and piety to God Almighty, as well as broaden the horizons of religious life, to form students who have a noble character, think philosophically, behave rationally and dynamically and have broad views, taking into account the demands for respect within one community, and in the relationship of inter-religious harmony. Lecture activities involve lecture models, dialogues, and paper presentations. Evaluation is done through written notes, assignments, reports, and presentations.

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MKU6203

Christian Education

The Christian Religious Education course is mandatory for every Christian student in all study programs, weighing 3 credit hours. This course is designed to strengthen faith and piety to God Almighty, as well as broaden the horizons of religious life, to form students who have a noble character, think philosophically, behave rationally and dynamically and have broad views, taking into account the demands for respect within one community, and in the relationship of inter-religious harmony. Lecture activities involve lecture models, dialogues, and paper presentations. Evaluation is done through written notes, assignments, reports, and presentations.

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MKU6204

Buddhist Education

The subject of Buddhist Education is compulsory for every Buddhist student in all study programs, weighing 3 credit hours. This course is designed to strengthen faith and piety to God Almighty, as well as broaden the horizons of religious life, to form students who have a noble character, think philosophically, behave rationally and dynamically and have broad views, taking into account the demands for respect within one community, and in the relationship of inter-religious harmony. Lecture activities involve lecture models, dialogues, and paper presentations. Evaluation is done through written notes, assignments, reports, and presentations.

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MKU6205

Hindu Education

Religion, as understood by most Hindus, is not a theory to be memorized, nor is it mere dogma and not meaningless words. Religion is a demand that contains a set of values that, if practiced, will be very useful for himself and others. The Hindu Religious Education course is mandatory for every Hindu student in all study programs, weighing 3 credit hours. This course is designed to strengthen faith and piety to God Almighty, as well as broaden the horizons of religious life, to form students who have a noble character, think philosophically, behave rationally and dynamically and have broad views, taking into account the demands for respect within one community, and in the relationship of inter-religious harmony. Lecture activities involve lecture models, dialogues, and paper presentations. Evaluation is carried out in writing, assignments, reports, and presentations.

MKU6206

Confucian Education

The Confucian Religious Education course covers the urgency of religion in everyday life with the right attitude. This course includes understanding the sources of Confucian law, knowing the history of Confucianism, being able to carry out the Holy Way brought by the Great Teachings (Thai Hak), and the role of Confucianism in the development of science and technology.

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MKU6207

Civic Education

The Citizenship Education course is mandatory for all undergraduate and D3 program students, weighing 2 credit hours. This course equips students with essential knowledge and skills regarding the relationship between citizens and the state, as well as preliminary education in defending the state so that they become citizens who can be relied on by their nation and state. This course examines: (1) Rights and obligations of citizens (2) Preliminary education to defend the country (3) Indonesian Democracy (4) Human Rights (5) Archipelago insight as an Indonesian Geopolitics (6) National Resilience as an Indonesian Geostrategy (7) National Politics and Strategy as the Implementation of Indonesia's Geostrategy.

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MKU6211

English

This course covers four skills in English, namely listening, reading, speaking, and writing. This course includes the rules of English grammar, communication in mathematics orally, communication in mathematics in writing, listening mathematics video, presenting mathematics video, translating mathematics texts from English to Indonesian and vice versa, and rewriting mathematics articles. In addition, students also get the knowledge and practice of TOEFL exercises.

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FMI6202

Statistics

This course contains an introduction to statistical investigations, significance, generalization, estimation, causation, comparison of two proportions, comparison of two averages, paired data, comparison of more than two proportions, comparison of more than two averages, and two quantitative variables.

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STA6301

Logic and Set

This course studies statistical reasoning related to propositional logic, information deduction, argument validity, proof methods, and predicate logic. In addition, set theory, relations, and functions are also studied in this course.

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STA6302

Basic Calculus for Statistics

The Basic Calculus for Statistics course discusses the concepts of real number systems and inequalities, coordinate systems and functions, function limits and function continuity, function derivatives, derivative searches, derivatives and stationary points, derivative applications in statistics, indefinite integrals, integration techniques, and certain integrals.

STA6303

Linear Algebra and Matrices

This course covers matrices, vectors, matrix and vector operations, systems of linear equations, Euclid space, rank matrices, orthogonality, determinants, eigenvalues and eigenvectors, singular values and decomposition, quadratic forms, Kronecker multiplication and related operations.

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MKU6212

Digital Transformation

This course contains the final development of digital technology, general concepts of computer programming, describing syntax, semantics, and runtime environment Python Programming Language, general concepts of computer programming (using the Python programming language), the role of Internet of Things, Big Data, and Artificial Intelligence in the Industrial Age. 4.0, the concept of Big Data, the concept and application of Artificial Intelligence, and examples of the application of Machine Learning.

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STA6204

History and Ethics of Statistics

This course examines the history of statistics and ancient probability theory; the use of Mathematics and Computers in the development of statistics and probability; application of statistics and probability in various fields. In relation to ethics, it examines the meaning and scope of ethics as well as various ethics in statistical procedures: ethics in data collection and storage, ethics in data processing and presentation, ethics in drawing conclusions and providing recommendations, ethics in statistical consulting, ethics in developing statistical methods, and the formulation of the Statistics professional code of ethics.

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MKU6208

Pancasila

This lecture discusses the foundations and objectives of Pancasila Education, Pancasila in the context of the history of the struggle of the Indonesian people, Pancasila as a philosophical system, Pancasila as political ethics and national ideology, Pancasila in the context of the Republic of Indonesia's state administration and Pancasila as a paradigm of life in society, nation and state.

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MKU6209

Bahasa Indonesia

This course aims to equip students to have the competence to use Indonesian in writing scientific papers. The topics covered include historically Indonesian, the position and function of Indonesian, Indonesian grammar, paragraph development, paragraph types, reasoning in paragraphs, scientific papers, scientific writing formats, reference writing, and bibliography writing. Learning activities include face-to-face lectures, discussions, and structured assignments. Evaluation is carried out by written tests and structured assignments.

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MKU6213

Creativity, Innovation, and Entrepreneurship

This lecture discusses entrepreneurship which includes the role of entrepreneurs in the state, the reasons undergraduates are required to be entrepreneurs, the role of the government in creating entrepreneurship, the definition of entrepreneurship, the skills needed for entrepreneurship, entrepreneurial attitudes and profiles, entrepreneurship as a complete human being, the causes of business failure. The course also examines techniques for developing creativity, issues, and problems encountered in entrepreneurial practice.

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STA6305

Data Analysis and Visualization

This course includes an introduction to R, the chi-square test for univariate categorical data, the squared test for bivariate categorical data, simple linear regression, multiple linear regression, one-way analysis of variance, two-way analysis of variance, basic data manipulation, data manipulation, merging multiple data frames, data cleaning, categorical data visualization, continuous data visualization, simultaneous categorical and continuous data visualization, map visualization.

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STA6306

Nonparametric Statistics

This course covers Nonparametric of one- and two-sample t-tests and analysis of variance; sign test, median test, Wilcoxon test, and Kruskal-Wallis and Friedman test, independence test; nonparametric regression and nonparametric density estimation; modern nonparametric techniques; nonparametric confidence interval estimation.

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STA6307

Advanced Calculus for Statistics

This course covers improper integrals, concepts about infinite sequences and series, Taylor series, two-variable functions, limits and continuity of two-variable functions, derivatives of multiple-variable functions, multiple integrals and double integrals in Cartesian coordinates.

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STA6308

Regression Analysis

This course covers the methodology for fitting a simple linear regression model (SLR), statistical inference for the SLR model, diagnostics and verification of assumptions and remedial SLR models, solving the SLR model with matrix algebra, methodologies for fitting multiple linear regression models (MLR), statistical inference for MLR models, statistical inference for MLR models, predictors of binary and qualitative indicators, model fitting diagnostics, model selection and model building.

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STA6309

Algorithm and Statistical Programming

This course discusses problem solving (mathematics), the preparation and presentation of the solution steps, as well as making programs using the Python Programming Language. The topics studied include: (1) problem solving, (2)  algorithms and how to present them, (3) Python language program structure, inputoutput commands, identifiers, (4) data types, variables, and arithmetic and logical operations, (5) control flow and decision-making structure, (6) loop, (7) advanced data types: list, tuple, dictionary, (8) function, (9) file and exception, (10) data visualization in Python.

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MKU6216

Social Literacy and Humanity

This course contains the perspective of general education, which includes (1) Humans as cultural creatures; (2) Humans and civilization; (3) Humans as individuals and social beings; (4) Multiculturalism and equality; (5) Morality and law; (6) Humans and technology; (7) Humans and the environment; (8) ISBD in the challenges of globalization.

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STA6310

Experimental Design

This course covers the basic principles of experimental design, completely randomized design, complete group design, Latin square design, Graeco-Latin square design, balanced incomplete group design, two-factor factorial randomized design, more than two-factor factorial randomized design, two-factor factorial group design, split plot design, strip plot design, and response surface design.

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STA6311

Statistical Optimization

This course discusses the necessary conditions for first and second order, one-dimensional optimization methods (half interval search method, Fibonacci search method, Golden section search method, quadratic method, bisection method, Newton-Raphson method, secant method), steepest method. descent, Newton's method, conjugate gradient method, quasi-Newton's method.

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FMI6201

Study of Mathematics and Natural Sciences

This course discusses the basic methods of Mathematics and Natural Sciences (scientific method) in problem-solving and how/techniques to draw conclusions based on the correct rules of reasoning (Statistical logic). This study also covers the basic concepts of science and its latest developments.

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STA6312

Probability Theory

This course covers topics in probability theory, i.e. combinatorics, several definitions of probability, random variables and their distribution, properties of random variable, joint distribution of random variable, functions of random variable, sampling distribution, and central limit theorem.

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STA6314

Database for Statistics

This course provides an understanding and mastery of database concepts, relational data models, database formation and normalization techniques, the use of query language (SQL) for searching, sorting, filtering, deleting and updating data as well as creating database application programs in system development. computer-based data processing and the use of databases in information systems.

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STA6313

Sampling and Survey Techniques

This course outlines the objectives of the sample survey and its use in policy making; parameter estimation on simple random sample, layered random sample, systematic sample, and cluster sample; ratio estimation and regression; population size estimation; sampling method for online survey, online survey design.

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STA6316

Mathematical Statistics

This course discusses point estimation and the properties of point estimators, confidence intervals, the pivotal quantity method, general methods, large sample confidence intervals, small sample intervals, Bayesian interval estimation, and the concept of hypothesis testing, most powerful tests, uniformly most powerful tests, generalized likelihood ratio.

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STA6317

Categorical Data Analysis

This course includes data analysis with nominal and ordinal scale response variables; contingency table; inference on logistic regression models, multinominal regression, ordinal regression, and Poisson regression; model selection and evaluation; and its application.

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STA6315

Time Series Analysis

This course studies the basic aspects of forecasting, time series data patterns (trend, seasonal, cyclic, and irregular), the concepts of autocorrelation and partial autocorrelation, stationary and white noise, moving average and smoothing methods, time series decomposition, regression in the context of time series, Autoregressive Integrated Moving Average (ARIMA) model, application with statistical software and interpreting analysis results.

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STA6314

Statistical Computation

This course covers the main ideas of programming in statistical analysis numerically and graphically. Topics covered include data types and data structures, flow control and looping, creating functions, text manipulation, writing and calling functions, data scrapping, reading data from various sources, data processing, visualizing data, parameter estimation methods, sentiment analysis, text mining, bootstrap and jackknife, as well as handling big data.

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STA6319

Introduction to Multivariate Statistics

This course studies the concepts and aspects of multivariate statistics: random vectors and matrices, multivariate normal distribution, multivariate analysis of variance for two groups, multivariate analysis of variance for k-groups, assumptions in multivariate analysis of variance, factorial analysis of multivariate variance, analysis of covariance, and multivariate analysis of covariance.

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STA6326

Statistical Simulation

This course includes simulations for statistical inference. The topics discussed include the basics of simulation, simulation of sampling distributions of discrete and continuous probability distributions, simulations of the inference of means and proportions of one and two populations, simulations of simple and multiple linear regression, simulations of analysis of variance, statistical simulations. Robust, and simulation of stochastic processes (Markov chains, Poisson processes, birth and death processes).

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STA6322

Multivariate Statistics

This course includes multivariate linear regression models, principal component analysis, multidimensional scaling analysis, factor analysis, canonical correlation analysis, cluster analysis, and discriminant analysis. This course will provide a set of skills to analyze multivariate data with statistical software and interpret the results of the analysis.

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STA6327

Educational Statistics

This course contains path analysis, principal component analysis, exploratory factor analysis, confirmatory factor analysis, introduction to structural equation modelling, and item response theory, as well as its application to the field of education.

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STA6323

Statistical Machine Learning

This course studies the basic concept of machine learning, supervised learning, unsupervised learning and preprocessing, as well as model evaluation and improvement.

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STA6328

Artificial Neural Networks

This course contains theories, methods and problems in Artificial Neural Networks related with statistics, starting with the basics of artificial neural networks, perceptron networks, multilayer perceptron, backpropagation methods, artificial neural network algorithms and examples of the application of artificial neural networks in statistics.

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STA6327

Bayesian Statistics

This course contains the basic concepts of Bayesian, Bayesian inferences for discrete random variables, binomial proportions, Poisson, normal mean, difference between means, simple linear regression, normal with mean and variance. unknown, multivariate normal mean vector, and multiple linear regression.

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STA6325

Research Design

This course covers the process of preparing research using quantitative and qualitative approaches, identifying research problems; literature review; determining research objectives, formulation and hypotheses; quantitative data collection; analysis and interpretation of quantitative data; qualitative data collection; analysis and interpretation of qualitative data; research reporting and evaluation; experimental design; correlational design; survey design; grounded theory design; ethnographic design; narrative research design; mixed methods design; and action research design.

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STA6324

Data Mining for Statistics

This course discusses the concepts and understanding of data mining, data warehouse concepts and understanding, data mining life cycle, OLAP, data mining techniques, data mining applications and trends.

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STA6321

Linear Model

This linear model course studies vectors, random matrices and their properties, multivariate normal distribution and its properties, distribution of the quadratic form, simple linear regression, estimation on multiple regression, inference on multiple regression, multiple regression with random predictors.

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MKL6603

Internship (PKL)

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MKL6604

Community Services

This course is in the form of practice in the field for 1.5 months with locations in villages in the DIY and Central Java regions. Students practice developing character in the form of cooperation, respect for others, and so on. In addition, students practice socializing with residents, become motivators and are able to apply their knowledge to help solve problems in the community.

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TAM6801

Undergraduate Thesis

This course is a student's final project which is written in the form of a scientific paper as a result of a literature study or the result of the application of Statistics. The writing refers to the Thesis Final Assignment Guide. Students write their final thesis under supervise a lecturer in accordance with the topics the students are working on. The final product of this course is a thesis article published in the Statistics student journal or the proceedings of an international seminar indexed by Scopus or a reputable international journal.