BS Statistics
The Bachelor of Science in Statistics (BS STAT) is a four-year degree program with a total of 143 academic units in its curriculum which includes courses in statistics, mathematics, and computer science. The rest of the courses include elective and general education courses. The program is designed to make a BS Statistics graduate flexible through exposure to the basic sciences, to build a career in business, industry, academe or government, or to pursue graduate studies in statistics and its allied fields.
Admission Requirements
- New freshman students are admitted to the programs through the UPCAT/ UPCA.
- 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, UPLB.
- Non-UPLB students wishing to enter the program by transfer must apply in writing to the University Registrar.
Undergraduate Statistics Courses
COURSE | COURSE TITLE | DESCRIPTION | PREREQUISITE/S |
---|---|---|---|
STAT 101 | Statistical Methods | Analysis of measurements and discrete data; some nonparametric methods; simple linear regression and correlation analysis; analysis of variance and covariance | None |
STAT 135 | Logic and Matrix Algebra in Statistics | Basic concepts and methods in logic and matrix algebra useful in Statistics | None |
STAT 144 | Introductory Statistical Theory I | Probability models, operations on probability, random variables and random vectors; mathematical expectations; sampling from a probability distribution; statistical inference | MATH 28 |
STAT 145 | Introductory Statistical Theory II | Discrete and Continuous Probability Models; Generating Functions; Functions of Random Variables and Random Vectors; Sampling from Normal Populations; Large- sample Theory | STAT 144 |
STAT 146 | Introductory Statistical Theory III | Estimation; Testing of hypothesis and common parametric tests | STAT 145 |
STAT 147 | Introduction to the Theory of Nonparametric Statistics | Development of point and interval estimates and formulation of tests of hypothesis based on distribution-free statistics | STAT 145 |
STAT 148 | Introductory Bayesian Statistics | Theory of Bayesian methods and their applications | STAT 145 |
STAT 151 | Applied Regression and Correlation | Linear regression; correlation analysis; methods of model selection | STAT 135 |
STAT 156 | Introductory Time Series Analysis | Approaches to time series analysis; autocovariance and autocorrelation functions; linear stationary and non-stationary processes; forecasting, modelling and diagnostic checking; seasonal time series. | STAT 135 or COI |
STAT 157 | Financial Risk Analysis | Time series analysis in finance | STAT 156 |
STAT 162 | Experimental Designs | Principles 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. | None |
STAT 163 | Survey Designs | Introduction to sampling methods: simple random, stratified, unequal probability and multi-stage sampling, methods of estimation | STAT 144 |
STAT 164 | Statistics for the Biological Sciences | Statistical 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 | None |
STAT 165 | Categorical Data Analysis | Analysis 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 101 |
STAT 166 | Statistics for the Social Sciences | Sampling 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. | None |
STAT 167 | Statistical Quality Control | Types of variables, frequency distribution, descriptive measures of a distribution, control charts, process capability, introduction to designed experiments for process improvement, acceptance sampling | None |
STAT 168 | Response Surface Methodology | Experimental designs and analysis for estimating response surfaces | None |
STAT 173 | Survey Operations | Planning, execution and analysis of surveys | STAT 163 |
STAT 174 | Introductory Biostatistics | Statistical methods and models in analyzing data from the health sciences | None |
STAT 175 | Analysis of Multivariate Data | Analysis 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 101 |
STAT 181 | Statistical Computing | General Methods of Approximation, Approximating Probabilities and Percentage Points, Resampling | COI |
STAT 182 | Statistical Packages | Statistical packages in data processing and analysis | STAT 101 |
STAT 183 | Introductory Data Analytics | Statistical methods in handling real massive datasets and their applications | STAT 151, STAT 175, CMSC 21 |
STAT 190 | Special Problem | COI | |
STAT 191 | Special Topics | Topics: • Small-area Estimation • Environmental Risk Analysis | COI |
STAT 192.1 | Statistical Consulting Laboratory | Application of statistics in addressing client’s problems | COI |
STAT 198 | Practicum | COI | |
STAT 199 | Undergraduate Seminar | COI |
- Currently enrolled students may contact [email protected] for any concerns related to registration of courses.