May 04, 2024  
2022-2023 Academic Catalog 
    
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2022-2023 Academic Catalog [ARCHIVED CATALOG]

Course Descriptions

Introduction

This section of the catalog offers an alphabetical listing of undergraduate and graduate courses offered at Georgia Southern University, along with the college in which that course is taught. Undergraduate courses, in general, begin with a 1, 2, 3, or 4. Courses numbered “5000” are also undergraduate courses. Graduate courses, in general, begin with a 6, 7, 8, or 9. Courses numbered “5000” followed by a “G” are also graduate courses. (See “Course Numbering” below). Prerequisites, co-requisites, and cross listings are noted at the end of each description.

Course Numbering System

In general, the first digit of the course corresponds to the level of the class.

1 Freshman
2 Sophomore
3 Junior
4 Senior
5 Dual Undergraduate/Graduate
6 Lower Division Graduate
7-8 Upper Division Graduate
9 Doctoral Level Graduate

A 5000 course number followed by a “G” indicates a Graduate course. 

The fourth digit indicates the sequence of the course.

College Abbreviations

CAH College of Arts and Humanities
CBSS College of Behavioral and Social Sciences
COB Parker College of Business
COE College of Education
CEC Allen E. Paulson College of Engineering and Computing
CHP Waters College of Health Professions
COPH Jiann-Ping Hsu College of Public Health
COSM College of Science and Mathematics
VPAA Office of Vice President for Academic Affairs
Interdisciplinary Courses offered by more than one department and/or college

 
 

STAT Statistics
  

  • STAT 996 - Support for Elementary Statistics (2 Credit Hours)

    Lecture Hours: 2 Lab Hours: 0
    This Learning Support course provides corequisite support for students enrolled in STAT 1401  - Elementary Statistics. Topics will parallel topics being studied in STAT 1401  and the course will provide support for the essential skills needed to be successful in STAT 1401 . Taken with STAT 1401 , topics to be covered will include descriptive statistics, probability theory, confidence intervals, hypothesis testing, and other selected statistics topics.

    Corequisite(s): STAT 1401 .
  

  • STAT 1401 - Elementary Statistics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    This is a non-calculus based introduction to statistics. Course content includes descriptive statistics, probability theory, confidence intervals, hypothesis testing, and other selected statistical topics.

    Cross Listing(s): MATH 1401 .
  

  • STAT 1402 - Elementary Statistics II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    A continuation of STAT 1401 . The focus is on inferential procedures to compare the same characteristic between two or more populations and inferential procedures to investigate the relationship between two or more variables from the same population. Topics include tests of association, regression, correlation, and analysis of variance, and use of statistical software.

    Prerequisite(s): A minimum grade of “C” in STAT 1401  or MATH 1401 .
  

  • STAT 2232 - Introduction to Statistics II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    A continuation of STAT 2231. The focus is on inferential procedures to compare the same characteristic between two or more populations and inferential procedures to investigate the relationship between two or more variables from the same population. Topics include tests of association, regression, correlation, and analysis of variance. The statistical software package SPSS is used.

    Prerequisite(s): A minimum grade of “C” in STAT 1401  or MATH 1401 .
  

  • STAT 3130 - Applied Statistics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    An introductory course in applied statistics for students in the natural sciences, social sciences, health and professional studies, technology, and business. The material covered will provide an introduction to statistical concepts and terminology while focusing on descriptive and inferential methods of data analysis. Both parametric and nonparametric methods are presented for the analysis of central tendency, variability, proportions, and categorical data. Topics covered also include regression and correlation.

    Prerequisite(s): MATH 1111 .
  

  • STAT 3338 - Statistical Inference (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    A course covering sampling distributions, methods of estimation for point and interval estimation, testing of statistical hypotheses, contingency tables, and goodness-of-fit. The content of this course will satisfy the Mathematical Statistics VEE (Validation by Educational Experience) for the Society of Actuaries.

    Prerequisite(s): A minimum grade of “C” in MATH 3337 .
  

  • STAT 4090 - Selected Topics in Statistics (1-3 Credit Hours)

    Lecture Hours: 1-3 Lab Hours: 0-2
    Specialized study in a selected area of Statistics.

    Prerequisite(s): Permission of instructor required.
  

  • STAT 4890 - Directed Study in Statistics (1-3 Credit Hours)

    Lecture Hours: 1-3 Lab Hours: 0-2
    Directed study under faculty supervision. Well-prepared statistics students may be permitted to enroll in an independent study upon the recommendation of a Statistics faculty member.

    Prerequisite(s): Permission of instructor and Department Chair required.
  

  • STAT 5130 - Sampling and Survey Methods (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    An introduction to the design and analysis of sample surveys suitable for students in business, social sciences, and biological sciences in addition to the mathematical sciences. Comparison of simple random sampling, stratified, systemic, cluster and multistage sampling. Emphasis on appropriate sample type and estimation of parameters.

    Prerequisite(s): A minimum grade of “C” in STAT 1401  or MATH 1401 .
    Cross Listing(s): STAT 5130G .
  

  • STAT 5130G - Sampling and Survey Methods (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    An introduction to the design and analysis of sample surveys suitable for students in business, social sciences, and biological sciences in addition to the mathematical sciences. Comparison of simple random sampling, stratified, systemic, cluster and multistage sampling. Emphasis on appropriate sample type and estimation of parameters. Graduate students will complete assignments beyond the scope of the undergraduate requirements. These assignments require a higher-level mastery of the subject matter and additional deliverables representative of graduate-level work, as determined by the instructor.

    Prerequisite(s): A minimum grade of “C” in STAT 1401  or MATH 1401 .
    Cross Listing(s): STAT 5130 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 5531 - Statistical Methods I (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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, simple linear regression and correlation, and resampling methods including bootstrapping. Both parametric and nonparametric methods are presented for the analysis of central tendency, variability, proportions and categorical data.

    Prerequisite(s): A minimum grade of “C” in MATH 3337 .
    Cross Listing(s): STAT 5531G .
  

  • STAT 5531G - Statistical Methods I (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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, simple linear regression and correlation, and resampling methods including bootstrapping. Both parametric and nonparametric methods are presented for the analysis of central tendency, variability, proportions and categorical data. Graduate students will be required to complete advanced level assignments in an area beyond the scope of the undergraduate requirements that demonstrates a higher level of mastery in the subject matter with additional required deliverables representative of graduate level work, as determined by the instructor.

    Prerequisite(s): A minimum grade of “C” in MATH 3337 .
    Cross Listing(s): STAT 5531 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 5532 - Statistical Methods II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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. Suitable for students in business administration, economics, and the social, health and biological sciences.

    Prerequisite(s): A minimum grade of “C” in STAT 5531 .
    Cross Listing(s): STAT 5532G .
  

  • STAT 5532G - Statistical Methods II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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. Suitable for students in business administration, economics, and the social, health and biological sciences. Graduate students will complete assignments beyond the scope of the undergraduate requirements. These assignments require higher-level mastery of the subject matter and additional deliverables representative of graduate-level work, as determined by the instructor.

    Prerequisite(s): A minimum grade of “C” in STAT 5531 .
    Cross Listing(s): STAT 5532 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 5660 - Statistical Data Analytics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    The course will apply concepts learned in diverse areas of mathematics to data analysis. Topics include clustering and classification, data cleaning, text analysis and document similarities, frequent itemsets and association rules, neural networks, support vector machines, and decision trees. This class has a primary focus on the underlying mathematical theory, with a secondary focus on application. Students will be introduced to R and RStudio for data storage, manipulation, and visualization.

    Prerequisite(s): A minimum grade of “C” in the following: MATH 2160 , MATH 2243 , and at least one of MATH 3337  or STAT 5531 .
    Cross Listing(s): STAT 5660G , MATH 5660 , MATH 5660G .
  

  • STAT 5660G - Statistical Data Analytics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    The course will apply concepts learned in diverse areas of mathematics to data analysis. Topics include clustering and classification, data cleaning, text analysis and document similarities, frequent item sets and association rules, neural networks, support vector machines, and decision trees. This class has a primary focus on the underlying mathematical theory, with a secondary focus on application. Students will be introduced to R and RStudio for data storage, manipulation, and visualization. Graduate students will complete assignments beyond the scope of the undergraduate requirements. These assignments require higher-level mastery of the subject matter and additional deliverables representative of graduate-level work, as determined by the instructor.

    Prerequisite(s): A minimum grade of “C” in the following: MATH 2160 , MATH 2243 , and at least one of MATH 3337  or STAT 5531 .
    Cross Listing(s): STAT 5660 , MATH 5660 , MATH 5660G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7090 - Selected Topics in Statistics (1-3 Credit Hours)

    Lecture Hours: 1-3 Lab Hours: 0-2
    Selected study in a selected area of Statistics.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7130 - Applied Multivariate Statistical Analysis (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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, discriminate analysis and cluster analysis.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7132 - Applied Nonparametric Statistics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    Review of probability and statistical inference; binomial, quantile and sign tests; contingency tables; methods based on ranks.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7134 - Applied Regression Analysis (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    Simple and multiple linear regression, model selection, residual analysis, influence diagnostics, transformation of data to fit assumptions, multicollinearity and an introduction to nonlinear regression.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7135 - Analysis of Discrete Data (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    The study of discrete univariate and multivariate distributions and generating functions, two-way and higher dimensional contingency tables, chi-squared and other goodness-of-fit tests, Cochran-MantelHanzel procedure, binary and multinomial response models, log-linear models, theoretical foundations for the generalized linear models, mixed generalized linear models, longitudinal and spatial data analysis.

    Prerequisite(s): Completion of STAT 7331  and STAT 5531G , with a minimum grade of “C”.
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7231 - Design of Experiments I (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7232 - Design of Experiments II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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. Multiresponse experiments, nonlinear response surface models, and mixture designs are also studied.

    Prerequisite(s): Completion of STAT 7231 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7234 - Statistical Process Control (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    Philosophy of statistical process control is studied along with SPC techniques of control charts, process-capability, designed experiments and acceptance sampling.

    Prerequisite(s): Completion of STAT 5531  or STAT 5531G .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7331 - Mathematical Statistics I (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    Random variables, density functions, mathematical expectation, discrete and continuous distributions, moments and moment-generating functions and limiting distributions.

    Prerequisite(s): Completion of MATH 2242  and MATH 3337 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7332 - Mathematical Statistics II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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.

    Prerequisite(s): Completion of STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7430 - Actuarial Mathematics (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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 and theory of pension funding.

    Prerequisite(s): Completion of STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7432 - Applied Stochastic Processes (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    Poisson process, renewal theory, Markov chains, Brownian motion, random walks and Martingales and stochastic order relations.

    Prerequisite(s): A minimum grade of “C” in STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7434 - Applied Time Series Analysis (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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 non-stationary ARIMA models along with forecasting models.

    Prerequisite(s): Completion of STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7436 - Reliability Analysis (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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 and accelerated life testing.

    Prerequisite(s): Completion of STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7530 - Statistical Computing I (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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.

    Prerequisite(s): Completion of STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7532 - Statistical Computing II (3 Credit Hours)

    Lecture Hours: 3 Lab Hours: 0
    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.

    Prerequisite(s): Completion of STAT 5532G  or STAT 5532G  and STAT 7331 .
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7610 - Graduate Seminar (1 Credit Hour)

    Lecture Hours: 1 Lab Hours: 0
    Students will research topics related to their major/concentration, under supervision of one or more faculty members. Each student will present results on topics of interest to the class on new developments in mathematical sciences, or on their research project. Faculty members also may present lectures for the benefit of the students.

    Cross Listing(s): MATH 7610 .
    Restriction(s): NO Undergraduate Level Students
    Is Course Repeatable: Course may be repeated up to a maximum of 3 credit hours to be counted toward the M.S. in Mathematics.
  

  • STAT 7890 - Directed Study in Statistics (1-3 Credit Hours)

    Lecture Hours: 1-3 Lab Hours: 0-2
    Directed study under faculty supervision.

    Prerequisite(s): Permission of instructor and Department Chair.
    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7895 - Research (1-3 Credit Hours)

    Lecture Hours: 0 Lab Hours: 0
    Graduate students will conduct a program of independent research under the direction of a thesis advisor or an advisory committee on a topic in Statistics. Results of the research will be presented as a thesis in MATH 7999  for partial fulfillment of the requirement of the Master of Science Degree in Mathematics with an emphasis in Statistics.

    Restriction(s): NO Undergraduate Level Students
  

  • STAT 7899 - Research Project in Statistics (1-6 Credit Hours)

    Lecture Hours: 1-6 Lab Hours: 0-4
    Research project addressed toward a real world problem.

    Prerequisite(s): Permission of project advisor and Department Chair required.
    Restriction(s): NO Undergraduate Level Students