COURSES
ACCEPTABLE FOR GRADUATE CREDIT
FOR THE
MASTER OF SCIENCE
WITH A MAJOR IN MATHEMATICS
The courses in this list can be counted toward the requirements of the
Master of Science in Mathematics, with a concentration in Statistics.
Other courses listed in the Graduate Catalog under Statistics are for
other graduate degrees.
All requirements of the Department of Mathematical Sciences and the
College of Graduate Studies of Georgia Southern University must be
satisfied, including the distribution of the credit hours (namely that
at least 1/2 of the required 36 credit hours be at the 7xxx level).
All courses are 3 credits (unless otherwise indicated)
STATISTICS
STAT 5330G INTRODUCTION TO MATHEMATICAL STATISTICS
An introductory course intended to present a solid foundation in
statistical theory, and, at the same time, to provide an indication of
the relevance and importance of the theory in solving practical
problems in the real world. Topics include, moments and
moment-generating functions, point and interval estimation, test of
statistical hypothesis, contingency tables and goodness-of-fit,
nonparametric methods, and introduction to linear models. This course
covers part of the material outlined in the Society of Actuaries'
course 110.
Prerequisites: MATH 3337 (Probability) (minimum grade of C).
STAT 5531G STATISTICAL METHODS I
This is the first of a two course sequence in applied statistics. The
material covered will provide an introduction to statistical concepts
and terminology while focusing on descriptive and inferential methods
of data analysis. Topics include descriptive statistics, parameter
estimation, tests of significance, confidence intervals, analysis of
variance, and simple linear regression and correlation. Both parametric
and nonparametric methods are presented for the analysis of central
tendency, variability, proportions, and categorical data.
Prerequisites: MATH 3337 (Probability) (minimum grade of C)
STAT 5532G STATISTICAL METHODS II
This is the second of a two course sequence in applied statistics. The
material covered will provide an introduction to the ideas of linear
models and experimental design while focusing on methods of data
analysis using Regression and Analysis of Variance. Topics include
multiple regression analysis, analysis of variance with multiple
classification, analysis of covariance, repeated measures analysis of
variance, multiple comparison techniques, and diagnostic procedures and
transformations. The course is also suitable for students in business
administration, economics, and the social, health and biological
sciences.
Prerequisites: A minimum grade of C in STAT 5531 (STATISTICAL METHODS
I)or, with permission of the instructor, a one semester introduction to
applied statistics at the junior level or above.
STAT 7090 SELECTED TOPICS IN STATISTICS
Specialized study in a selected area of Statistics. (1 to 3 credit
hours)
Prerequisites: STAT 5531 (STATISTICAL METHODS I) and permission of
instructor.
STAT 7130 APPLIED MULTIVARIATE STATISTICAL ANALYSIS
Estimating and inference from the Multivariate normal distribution;
Hotelling's T 2 ; multivariate analysis of variance; multivariate
regression; multivariate experimental design; principle component
analysis; factor analysis; discriminant analysis; cluster analysis.
Prerequisites: STAT 5531 (STATISTICAL METHODS I).
STAT 7132 APPLIED NONPARAMETRIC STATISTICS
Review of probability and statistical inference; binomial, quantile,
and sign tests; contingency tables; methods based on ranks.
Prerequisites: STAT 5531 (STATISTICAL METHODS I).
STAT 7134 APPLIED REGRESSION ANALYSIS
Simple and multiple linear regression, model selection, residual
analysis, influence diagnostics, transformation of data to fit
assumptions, multicollinearity, and an introduction to nonlinear
regression.
Prerequisites: STAT 5531 (STATISTICAL METHODS I).
STAT 7231 DESIGN OF EXPERIMENTS I
Various statistically designed experiments are introduced including
randomized blocks designs, Latin squares, incomplete block designs,
factorial and fractional factorial designs with and without
confounding, and nested designs.
Prerequisites: STAT 5531 (STATISTICAL METHODS I) or equivalent.
STAT 7232 DESIGN OF EXPERIMENTS II
Response surface methodology is introduced. First- and second-order
models and designs are studied which includes determining optimum
conditions and methods of estimating response surfaces. Multi-response
experiments, nonlinear response surface models, and mixture designs are
also studied.
Prerequisites: STAT 7231 (DESIGN OF EXPERIMENTS I).
STAT 7234 STATISTICAL PROCESS CONTROL
Philosophy of statistical process control is studied along with SPC
techniques of control charts, process-capability, designed experiments,
and acceptance sampling.
Prerequisites: STAT 5531 (STATISTICAL METHODS I).
STAT 7331 MATHEMATICAL STATISTICS I
Random variables, density functions, mathematical expectation, discrete
and continuous distributions, moments and moment-generating functions,
and limiting distributions.
Prerequisites: MATH 2242 (Calculus II) and MATH 3337 (Probability).
STAT 7332 MATHEMATICAL STATISTICS II
Rigorous introduction/development of interval estimation, test of
significance, comparison of k means, randomized block design, multiple
comparison procedures, nonparametric test, and linear regression. The
general linear model will be introduced.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I ).
STAT 7430 ACTUARIAL MATHEMATICS
Survival distributions and life tables; life insurance; life annuities;
net premiums; multiple life functions; multiple decrement models;
valuation theory for pension plans; collective risk models; population
theory; theory of pension funding.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I ).
STAT 7432 APPLIED STOCHASTIC PROCESSES
Poisson process; renewal theory; Markov chains; Brownian motion; random
walks and Martingales; stochastic order relations.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I).
STAT 7434 APPLIED TIME SERIES ANALYSIS
Basic ideas of stochastic model building techniques with applications
are discussed. Properties of the autocorrelation function and the
spectrum of stationary processes are investigated. Models studied
include the linear stationary ARMA and linear nonstationary ARIMA
models along with forecasting models.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I).
STAT 7436 RELIABILITY ANALYSIS
Probabilistic models for the reliability of coherent systems;
statistical models for lifetimes of components and repairable systems,
including the nonhomogeneous Poisson process; reliability estimation
and prediction; MIL standards; accelerated life testing.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I).
STAT 7530 STATISTICAL COMPUTING I
Basic computer organization and computer arithmetic are investigated.
Programming languages and statistical software/packages are explored.
Methods for approximating cumulative distribution function and
percentage points of a probability distribution are studied including
nonparametric procedures. Multiple comparison procedures are also
examined. Random number generation and statistical tests for testing
random number generators are explored.
Prerequisites: STAT 7331 (MATHEMATICAL STATISTICS I).
STAT 7532 STATISTICAL COMPUTING II
Various computational methods in linear algebra as applied to such
statistical methods as multiple linear regression, designed
experiments, multivariate analysis, and the general linear model.
Further topics include computational methods for unconstrained
optimization, nonlinear regression, and model fitting based on criteria
other than least squares.
Prerequisites: STAT 5532 and STAT 7331 (MATHEMATICAL STATISTICS I).
STAT 7890 DIRECTED STUDY IN STATISTICS
Directed study under faculty supervision. (1 to 3 credit hours)
Prerequisites: Permission of Instructor and Department Chair.
STAT 7899 RESEARCH PROJECT IN STATISTICS
Research project addressed toward a real world problem. (1 to 6 credit
hours)
Prerequisites: Consent of project advisor and permission of Department
Chair.
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