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.

See here INSTAT’s BS Statistics Program Specifications.

Admission Requirements

Undergraduate Statistics Courses

STAT 101Statistical MethodsAnalysis of measurements and discrete data; some nonparametric methods; simple linear regression and correlation analysis; analysis of variance and covarianceNone
STAT 135Logic and Matrix Algebra in StatisticsBasic concepts and methods in logic and matrix algebra useful in StatisticsNone
STAT 144Introductory Statistical Theory IProbability models, operations on probability, random variables and random vectors; mathematical expectations; sampling from a probability distribution; statistical inferenceMATH 28
STAT 145Introductory Statistical Theory IIDiscrete and Continuous Probability Models; Generating Functions; Functions of Random Variables and Random Vectors; Sampling from Normal Populations; Large- sample TheorySTAT 144
STAT 146Introductory Statistical Theory IIIEstimation; Testing of hypothesis and common parametric testsSTAT 145
STAT 147Introduction to the Theory of Nonparametric StatisticsDevelopment of point and interval estimates and formulation of tests of hypothesis based on distribution-free statisticsSTAT 145
STAT 148Introductory Bayesian StatisticsTheory of Bayesian methods and their applicationsSTAT 145
STAT 151Applied Regression and CorrelationLinear regression; correlation analysis; methods of model selectionSTAT 135
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 135 or COI
STAT 157Financial Risk AnalysisTime series analysis in financeSTAT 156
STAT 162Experimental DesignsPrinciples 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 163Survey DesignsIntroduction to sampling methods: simple random, stratified, unequal probability and multi-stage sampling, methods of estimationSTAT 144
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 dataNone
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 analysisSTAT 101
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.None
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 samplingNone
STAT 168Response Surface MethodologyExperimental designs and analysis for estimating response surfacesNone
STAT 173Survey OperationsPlanning, execution and analysis of surveysSTAT 163
STAT 174Introductory BiostatisticsStatistical methods and models in analyzing data from the health sciencesNone
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 analysisSTAT 101
STAT 181Statistical ComputingGeneral Methods of Approximation, Approximating Probabilities and Percentage Points, ResamplingCOI
STAT 182Statistical PackagesStatistical packages in data processing and analysisSTAT 101
STAT 183Introductory Data AnalyticsStatistical methods in handling real massive datasets and their applicationsSTAT 151, STAT 175, CMSC 21
STAT 190Special ProblemCOI
STAT 191Special TopicsTopics:
• Small-area Estimation
• Environmental Risk Analysis
STAT 192.1Statistical Consulting LaboratoryApplication of statistics in addressing client’s problemsCOI
STAT 198PracticumCOI
STAT 199Undergraduate SeminarCOI