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Applied Statistics
OPTION 41014
Prerequisite: Normally 60% in STM 312, 313, 322 and 323. The examination consists of six papers (not
less than 126 credits). No more than 2 papers (a maximum of 50 credits) may be selected from
Honours papers offered in Mathematics, Applied Mathematics, GIS
and/or Computer Science; any such selection must be made in
consultation with the Head of Department.
STM 502:
Multivariate Statistical Analysis
Contents:
Aspects of Multivariate Analysis; Matrix Algebra
and Random Variables; Sample Geometry and
Random Sampling; The Multivariate Normal
Distribution; Hotelling’s T2 test; Likelihood Ratio
Tests; Confidence Regions; One-way MANOVA.
(22 Credits)
STM 505:
Fixed Effects Modelling.
Contents:
The General Linear Model; The general linear
model expressed in terms of matrices;
Estimation and Inference; Analysis of variance and
covariance; Binary response variables.
(22 Credits)
STM 508:
Non-Parametric Statistics
Contents:
Introduction to non-parametric statistics; Tests of location; Tests of spread; Two-
sample procedures and their extensions; Tests based on empirical distribution
functions; Log-linear models. (22 Credits)
STS 501:
Operations Research.
Contents:
Linear Programming; The simplex method; Risk theory; Decision theory; Bayes Risk;
Minimax methods; Simulation; Stochastic models. (22 Credits)
STS 502:
Applied Time Series Analysis.
Contents:
Methods of describing time series; Trend, Seasonality and Error; Mathematical
Models for Time Series; Stationary and Second-order stationary process; ARIMA
processes; Box-Jenkins methods; Forecasting; The Frequency domain; Spectral
Analysis. (22 Credits)
STS 503:
Bayesian Statistics.
Contents:
Introduction to the fundamentals of Bayesian statistics; Subjective probability;
Representing prior knowledge; Conjugate priors; Improper priors; Markov chain
simulation. (22 Credits)
STS 504:
Applied Multivariate Statistics.
Contents:
Principal Components; Graphing Principal Components; Factor Rotation and Factor
Scores; Discrimination; Classification; Classification with two Multivariate Normal
Populations; Clustering. (22 Credits)
STS 505:
Random Effects Modelling.
Contents:
Exponential Family of Distributions; Generalized Linear Models; Random Effects
Models; Covariance Structures; Non-normal errors; Repeated Measures; Binary
data; Categorical data. (22 Credits)
STM 506:
Research Project.
Purpose :
To acquaint students with thorough understanding and knowledge of
research techniques such as proposal writing, data collection, data analysis,
scientific writing etc. of research reports in Statistics.
Contents:
Introduction: Design and analysis of an experiments; Sample-size calculations;
Questionnaire design; Sampling techniques; Literature searches.
Students will be expected to choose a topic in consultation with his/her supervisor.
(30 Credits)
Are you serious with
Statistics?
A good model is one that
accurately reflects the data
uses a relatively small
number of meaningful
independent variables to
predict a relatively large
proportion of the variability
in the dependent variable.
HONOURS COURSES
