BS Statistics


The Bachelor of Science in Statistics (BS STAT) is a four-year degree program with a total of 152 academic units in its curriculum which includes courses in Statistics, Math, Computer Science. The rest of the courses include legislated, foundation and General Education courses.


  • New freshman students are admitted to the programs through the UPCAT
  • An undergraduate student of UPLB who wishes to shift to the program must apply in writing to the Secretary of the College of Arts and Sciences
  • Non-UPLB students wishing to enter the program by transfer must apply in writing to the University Registrar.


Course Description
Course Flowchart
Course Brochure


STAT 1Elementary StatisticsBasic statistical concepts, frequency tables, summary measures, probability, sampling, estimation, testing of hypothesis, analysis of variance, regression and correlation, goodness-of-fit-tests and test of independence
STAT 101Statistical MethodsAnalysis of measurements and discrete data; some nonparametric methods; simple linear regression and correlation analysis; analysis of variance and covariance
STAT 135Logic and Matrix Algebra in StatisticsBasic concepts and methods in logic and matrix algebra useful in Statistics
STAT 144Introductory Statistical Theory IProbability models, operations on probability, random variables and random vectors; mathematical expectations; sampling from a probability distribution; statistical inference
STAT 145Introductory Statistical Theory IIDiscrete and Continuous Probability Models; Generating Functions; Functions of Random Variables and Random Vectors; Sampling from Normal Populations; Large- sample Theory
STAT 146Introductory Statistical Theory IIIEstimation; Testing of hypothesis and common parametric tests
STAT 147Introduction to the Theory of Nonparametric StatisticsDevelopment of point and interval estimates and formulation of tests of hypothesis based on distribution-free statistics
STAT 151Applied Regression and CorrelationLinear regression; correlation analysis; methods of model selection
STAT 156Introductory Time Series AnalysisApproaches to time series analysis; autocovariance and autocorrelation functions; linear stationary and non-stationary processes; forecasting, modelling and diagnostic checking; seasonal time series.
STAT 162Experimental Designs IPrinciples of experimental design; analysis of completely randomized design; randomized complete block design, latin square design, factorial experiments, split-plot design, treatment comparisons and analysis of covariance.
STAT 163Survey DesignsIntroduction to sampling methods: simple random, stratified, unequal probability and multi-stage sampling, methods of estimation
STAT 164Statistics for the Biological SciencesStatistical modelling of biological data; parametric and nonparametric tests for comparing means; analysis of relationships among variables; probit analysis; linear discriminant analysis; cluster analysis; analysis of categorical data
STAT 165Categorical Data AnalysisAnalysis of proportions and percentages; measures and models of independence and associations; log-linear, logit, logistic and probit models for nominal and ordinal, binary and multinomial response data; analysis if repeated measures categorical response data; simple and multiple correspondence analysis
STAT 166Statistics for the Social SciencesSampling and survey operations; tests of hypothesis; nonparametric tests; analysis of one-way and two-way classification data; measures of associations and relationships; quantitative text analysis.
STAT 167Statistical Quality ControlTypes of variables, frequency distribution, descriptive measures of a distribution, control charts, process capability, introduction to designed experiments for process improvement, acceptance sampling
STAT 172Experimental designs IIAnalysis of Nested Experiments; Symmetric Factorials; Confounding; Response Surface Analysis; Experiments with Mixtures; Incomplete Block Designs and Lattices; Repeated Measures and Crossover Designs; Analysis of Similar Experiments
STAT 173Survey OperationsPlanning, execution and analysis of surveys
STAT 175Analysis of Multivariate DataAnalysis of data from multivariate normal populations; profile analysis; multivariate analysis of variance; multivariate regression analysis; correlations; canonical correlation analysis; path analysis; discriminant analysis; principal component analysis; factor analysis; cluster analysis
STAT 181Statistical Computing
STAT 182Statistical PackagesStatistical packages in data processing and analysis
STAT 190Special Problem
STAT 191Special TopicsTopics:
• Small-area Estimation
• Study Designs in Biostatistics and Epidemiology
• Environmental Risk Analysis
STAT 198Practicum
STAT 199Undergraduate Seminar