Course Catalog
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| Course code & No. | Course Title | Course Description | Offering Unit |
|---|---|---|---|
| Stat 100 | Calculus and Matrix Algebra for Statistics | Stat | |
| Stat 101 | Elementary Statistics | Stat | |
| Stat 102 | Intermediate Statistical Methods for Research | Stat | |
| Stat 110 | Probability and Statistics for Engineers | Stat | |
| Stat 114 | Descriptive Statistics | Stat | |
| Stat 115 | Basic Statistical Methods | Stat | |
| Stat 117 | Mathematics for Statistics | Stat | |
| Stat 121 | Probability Theory I | Stat | |
| Stat 122 | Probability Theory II | Stat | |
| Stat 124 | Introduction to Programming | Stat | |
| Stat 125 | Applications Software and Software Packages | Stat | |
| Stat 130 | Introduction to Mathematical Statistics for Computer Science | Stat | |
| Stat 131 | Parametric Statistical Inference | Stat | |
| Stat 132 | Nonparametric Statistical Inference | Stat | |
| Stat 133 | Bayesian Statistical Inference | Stat | |
| Stat 134 | Introduction to Scientific Writing in Statistics | Principles and methods in scientific writing in statistical studies | Stat |
| Stat 135 | Matrix Theory for Statistics | Stat | |
| Stat 136 | Introduction to Regression Analysis | Stat | |
| Stat 138 | Introduction to Sampling Designs | Probability and non-probability sampling techniques; complex surveys; variance estimation; treatment of missing data; applications to various contexts | Stat |
| Stat 142 | Introduction to Computational Statistics | Comtemporary themes in computational statistics; survey of computationally-intensive methods in statistics; advanced data management; SQL programming; resampling methods; simulations; macro programming; modeling applications | Stat |
| Stat 143 | Survey Operations | Stat, Stat | |
| Stat 144 | Introduction to Sampling Designs | Stat | |
| Stat 145 | Introduction to Time Series Analysis and Forecasting | Stat | |
| Stat 146 | Introduction to Exploratory Data Analysis | Stat | |
| Stat 147 | Introduction to Multivariate Analysis | Multivariate normal distribution; inference on mean vector and dispersion matrices; principal component analysis; factor analysis; cluster analysis; discriminant analysis; canonical correlation analysis; correspondence analysis and perceptual mapping; multivariate analysis of variance (MANOVA); applications to various contexts. | Stat |
| Stat 147 | Introduction to Multivariate Analysis | Stat | |
| Stat 148 | Introduction to Experimental Designs | Principles of experimentation; completely randomized design; randomized complete block design; Latin-square design; factorial experiments; confounding; incomplete blocks design; cross-over design; analysis of covariance; nested and split-plot designs; random effects; response surface methodology (RSM); applications to various contexts. | Stat |
| Stat 148 | Introduction to Experimental Designs | Stat | |
| Stat 149 | Introduction to Categorical Data Analysis | Stat | |
| Stat 191 | Special Topics in Biological and Medical Statistics | Stat | |
| Stat 191.1 | Introduction to Biostatistics | Stat | |
| Stat 192 | Special Topics in Business and Economic Statistics | Stat | |
| Stat 192.1 | Statistics in Market Research | Stat | |
| Stat 192.2 | Advanced Linear Models | Stat | |
| Stat 193 | Special Topics in Industrial and Physical Science Statistics | Stat | |
| Stat 193.1 | Introduction to Statistical Quality Control | Stat | |
| Stat 194 | Special Topics in Social and Psychological Statistics | Stat | |
| Stat 195 | Introduction to Mathematical Statistics | Stat | |
| Stat 197 | Special Topics in Statistics | Stat | |
| Stat 201 | Statistical Operations I | Stat | |
| Stat 207 | Statistical Inference for Data Science | Concepts in probability theory and sampling distributions; classical statistical inference; computational inference; principles of data science | Stat-BGC |
| Stat 208 | Programming for Data Analytics | Programming tools and methods for data analytics; modular and efficient programming; working with different data structures; high performance programming; applications | Stat-BGC |
| Stat 210 | Statistical Software | Stat | |
| Stat 211 | Statistical Computing | Stat | |
| Stat 217 | Computational Statistics | Optimization methods; random numbers and Monte Carlo methods; Markov Chain Carlo; resampling methods; recent approaches and methods in Computational Statistics | Stat-BGC |
| Stat 218 | Statistical Machine Learning | Applications of statistical machine learning; generalized linear models; supervised learning; unsupervised learning; kernel methods; support vector machines; neural networks; ensemble learning; contemporary topics | Stat-BGC |
| Stat 219 | Advanced Topics in Machine Learning | Advanced topics, extensions, and new areas or latest developments in machine learning; contemporary topics in and applications to artificial intelligence and data science | Stat-BGC |
| Stat 221 | Introductory Probability | Stat | |
| Stat 222 | Introduction to Statistical Inference | Stat | |
| Stat 223 | Applied Regression Analysis | Stat | |
| Stat 224 | Experimental Designs | Stat | |
| Stat 225 | Time Series Analysis | Stat | |
| Stat 226 | Applied Multivariate Analysis | Multivariate normal distribution; principal components analysis; biplots and h-plots; factor analysis; discriminant analysis; cluster analysis; canonical correlation analysis; graphical and data oriented techniques; applications | Stat |
| Stat 227 | Knowledge Discovery in Data | Frameworks and processes of knowledge discovery in data; data preprocessing; data exploration; data journalism and storytelling; ethics and privacy in data and analytics | Stat-BGC |
| Stat 230 | Special Topics in Mathematics for Statistics | Stat | |
| Stat 231 | Probability Theory | Probability spaces and random variables; probability distributions and distribution functions; mathematical expectation; convergence of sequences of random variables; laws of large numbers; characteristics functions | Stat |
| Stat 232 | Parametric Inference | Stat | |
| Stat 233 | Linear Models | Stat | |
| Stat 234 | Multivariate Analysis | Stat | |
| Stat 235 | Survey of Stochastic Processes | Stat | |
| Stat 240 | High Dimensional Data | High dimensional data; high dimensional data visualization; high dimensional data analysis; dimension reduction; pattern search; clustering; applications | Stat |
| Stat 241 | Nonlinear Regression | Stat | |
| Stat 242 | Econometric Methods | Stat | |
| Stat 243 | Categorical Data Analysis | Stat | |
| Stat 244 | Design and Analysis of Clinical Experiments | Stat | |
| Stat 245 | Survival Analysis | Stat | |
| Stat 246 | Response Surface Methods | Product design and development; optimal designs; response surface models; response surface optimization; applications | Stat |
| Stat 247 | Data Mining and Business Intelligence | Principles of data mining; methods of data mining; themes of data mining; applications of data mining in business intelligence | Stat |
| Stat 249 | Nonparametric Modeling | Smoothing methods; kernel smoothing; spline smoothing; regression trees; projection pursuit; nonparametric regression; cross-validation; scoring; high dimensional predictors; additive models; backfitting | Stat |
| Stat 250 | Sampling Designs | Concepts in designing sample surveys; non-sampling errors; simple random sampling; systematic sampling; sampling with varying probabilities; stratification, use of auxiliary information; cluster sampling; multi-stage sampling | Stat |
| Stat 251 | Survey Operations | Stat | |
| Stat 252 | Bootstrap Methods | Empirical distribution functions; resampling and nonparametric statistical inference; optimality of the bootstrap; bootstrap in hypothesis testing; bootstrap in confidence intervals; bootstrap in regressin models; bootstrap for dependent data | Stat |
| Stat 260 | Quantitative Risk Management | Market risk; financial time series; copulas; extreme value theory; credit risk models; operational risks | Stat |
| Stat 261 | Stochastic Calculus for Finance | Continuous-time model; Brownian motion; random walk; quadratic variation; Ito formula; Black-Scholes equation; risk-neutral measure; martingale representation theorem; fundamental theorems of asset pricing | Stat |
| Stat 262 | Nonparametric Statistics | Stat | |
| Stat 263 | Bayesian Analysis | Stat | |
| Stat 264 | Elements of Decision Theory | Stat | |
| Stat 265 | Robust Statistics | Stat | |
| Stat 266 | Applied Nonparametric Methods | Methods for single, two and k samples; trends and association; nonparametric bootstrap | Stat |
| Stat 267 | Advanced Applied Multivariate Analysis | Confirmatory factor analysis; multidimensional scaling; correspondence analysis; classification trees; CHAID; procrustes analysis; neural networks; structural equation modeling | Stat |
| Stat 268 | Advanced Time Series Analysis | Nonstationarity; cointegration; interventions models; state space models; transfer functions; frequency domain; panel data; nonparametric methods for time series; nonparametric prediction; AR-Sieve; block bootstrap | Stat |
| Stat 269 | Advanced Categorical Data Analysis | Probability structure of categorical data; modeling count data with heterogeneous mean; models for multinomial responses; postulation, estimation, evaluation of various parametrization of models for categorical data; assessment and handling of overdispersion in count data; clustered categorical data; advanced topics | Stat-BGC |
| Stat 270 | Exploratory Data Analysis | Stat | |
| Stat 271 | Statistical Quality Control | Stat | |
| Stat 272 | Reliability Theory | Stat | |
| Stat 273 | SIX SIGMA STATISTICS | DMAIC (define-measure-analyze-improve-control) methodology; statistical process control; process capability; failure mode and effects analysis (FMEA); measurement system analysis; optimization by experimentation; taguchi method | Stat |
| Stat 274 | Market Research | The marketing research; data and data generation in marketing research; analytical methods; consumer behavior modeling | Stat |
| Stat 275 | Economic Statistics | The Philippine Statistical System; surveys being regularly conducted by the system: questionnaire designs, sampling designs, estimators, issues; official statistics being generated: national accounts, consumer price index, input-output table, poverty statistics, leading economic indicators, seasonally adjusted series; statistical methods useful in generating official statistics | Stat |
| Stat 276 | Statistics for Geographic Information Systems | Stat | |
| Stat 277 | Statistics for Image Analysis | Stat | |
| Stat 280 | Special Fields of Statistics | Stat-BGC, Stat | |
| Stat 290 | Statistical Consulting | Stat | |
| Stat 298 | Special Problem | Stat | |
| Stat 299 | Special Project in Data Science | Integration and application of foundations, theories and methods of data analytics to address problems in industry, government, and other sectors; design and implementation of individual or group capstone project that is either project-oriented (engagement with and solution for a client) or research-oriented (work on own or client’s agenda) | Stat-BGC |
| Stat 300 | Master's Thesis | Stat | |
| Stat 301 | Theory of Probability I | Stat | |
| Stat 302 | Theory of Probability II | Stat | |
| Stat 303 | Stochastic Processes | Stat | |
| Stat 311 | Theory of Statistical Inference I | Stat | |
| Stat 312 | Theory of Statistical Inference II | Stat | |
| Stat 313 | Decision Theory | Stat | |
| Stat 321 | Asymptotic Methods for Statistics | Stat | |
| Stat 380 | Advanced Special Topics | Stat | |
| Stat 390 | Reading Course | Stat | |
| Stat 396 | Seminar | Stat | |
| Stat 400 | Dissertation | Stat |