MS Statistics

The Master of Science in Statistics (MS STAT) program is designed to provide the graduate student with a more extensive training in research and teaching through a well-balanced mixture of theory and applied courses. The program requires a minimum of 31 units consisting of: 6 units of core courses (STAT 241 and 242); at least 9 units of 200 level courses in statistics; at least 9 units of cognate courses; 1 unit of seminar; and 6 units of thesis. Cognate field may be pursued in demography, genetics, economics, plant breeding, animal science, computer science, management, food science, information technology, mathematics, engineering science and hydrology, and water resources. Applicants of the program must submit a duly accomplished application for admission form (GS Form No. 1) to the Graduate School, UP Los Baños, together with the following:

Applicants must also have a BS Statistics or its equivalent from an accredited university/college. These are evaluated by the Graduate Curriculum Committee of INSTAT based on the following criteria:

## MS Statistics Courses

Course Number
Course Title
Description
STAT 235
Mathematics in Statistics
Matrices; Transformations; Infinite Series; Inequalities; Generating functions; special functions
STAT 241
Statistical Theory I
Probability, random variables, probability distributions, expectations, moments, and characteristic functions; distribution functions of random variables; sampling distributions
STAT 242
Statistical Theory II
Parametric point and interval estimation; theory of hypothesis testing; introduction to linear models
STAT 250
Multivariate Statistical Methods
Multivariate normal populations; tests of hypothesis on means, multivariate analysis of variance; classification by linear discriminant function; inferences from covariance matrices; principal components; and factor analysis
STAT 251
Linear Models I
Multidimensional normal distribution; distributions of quadratic forms; full rank models; estimation and tests of hypotheses
STAT 252
Linear Models II
Linear models not of full rank; experimental design models and components-of-variance models; distributional properties of point estimators; tests of hypotheses
STAT 263
Sampling and Sample Surveys
Simple random, stratified, systematic, multistage and multiphase sampling; ratio and regression estimation; sampling with varying probabilities
STAT 264
Statistics for Epidemiology
Statistical methods in the collection, organization, presentation, analysis and interpretation of epidemiologic data
STAT 266
Time Series Analysis I
Stationary stochastic processes; covariance and autocorrelation functions; autoregressive and moving average processes
STAT 291
Special Topics
STAT 299