Undergraduate Curriculum & Courses
Undergraduate Curriculum:
Core Requirements: 27-28 Total Hours
Nonparametric Statistical Methods, Categorical Data Analysis - Choose 1:
| Course |
Title |
Hours |
| STA 4502 |
Nonparametric Statistical Methods |
3 |
| STA 4504 |
Categorical Data Analysis |
3 |
Linear Algebra - Choose 1:
| Course |
Title |
Hours |
| MAS 2103 |
Matrices & Vector Spaces |
3 |
| MAS 3114 |
Computational Linear Algebra |
3 |
| MAS 4105 |
Linear Algebra I |
4 |
The courses STA 4210-11 must be taken in sequence. STA 4212 may be taken
before or after STA 4210-11. It is recommended that STA 4321-22 be completed
by the time that the student finishes his/her Junior year. The three-course
sequence MAC 3472-74 (Honors Calculus I-III) may be substituted for MAC
3311-13.
Statistics Electives: 6 Total Hours (Choose
2)
| Course |
Title |
Hours |
| STA 4173 |
Biostatistics |
3 |
| STA 4222 |
Sample Survey Design |
3 |
| STA 4502 |
Nonparametric Statistical Methods (if not used in core) |
3 |
| STA 4504 |
Categorical Data Analysis (if not used in core) |
3 |
| STA 4664 |
Sample Survey Design |
3 |
| STA 4702 |
Multivariate Statistical Methods |
3 |
| STA 4821 |
Stochastic Processes |
3 |
Programming Electives: 3 Total Hours (Choose
1)
| Course |
Title |
Hours |
| CGS 3020 |
Introduction to CIS |
3 |
| CGS 2420 |
Computer Programming using FORTRAN |
3 |
| CGS 2425-25L |
Computer Programming for Engineers & Lab |
3 |
| CGS 3403 |
Computer Programming using COBOL |
3 |
| CGS 3460 |
Computer Programming using C |
3 |
| CGS 3462 |
Computer Programming using Pascal |
3 |
Additional Electives: 3 Total Hours (Choose
1)
| Course |
Title |
Hours |
| COT 4501 |
Computational Numerical Analysis |
3 |
| ESI 4312 |
Operations Research I |
3 |
| MAA 4102 |
Introduction to Advanced Calculus for Engineers I |
3 |
| MAA 4211 |
Advanced Calculus I |
3 |
| MAD 4401 |
Introduction to Numerical Analysis |
3 |
| MAS 4105 |
Linear Algebra I (if not in core) |
4 |
| MAS 4107 |
Linear Algebra II |
3 |
Undergraduate Course Descriptions:
**NOTE: A Schedule of Courses
is also kept by the Office of the University
Registrar.
| STA 3023 Introduction to Statistics 1. F, S, SS. |
| Credits: 3 |
Prereq: |
| Graphical and numerical descriptive measures, probability,
conditional probability, probability laws, discrete random variables, binomial
and normal random variables, sampling distributions, central limit theorem,
large and small sample confidence intervals for parameters associated with
a single population and for comparison of two populations. Hypothesis testing
for large and small samples. (M) |
| STA 3024 Introduction to Statistics 2. F, S, SS. |
| Credits: 3 |
Prereq: STA 3023 or equivalent. |
| An introduction to the analysis of variance. Nonparametric
statistical methods and applications. Analysis of count data: chi-square
and contingency tables. Simple and multiple linear regression methods with
applications. (M) |
| STA 3032 Engineering Statistics. F, S, SS. |
| Credits: 3 |
Prereq: MAC 2311 |
| A survey of the basic concepts in probability and statistics
with engineering applications. Topics include probability, discrete and
continuous random variables, estimation, hypothesis testing, and linear
and multiple regression. (M) |
| STA 3122 Statistics for the Social Sciences. F, S, SS.
|
| Credits: 3 |
Prereq: |
| Basic statistical concepts presented in a conceptual fashion,
emphasizing data collection and analysis rather than theory. Topics include
exploratory data analysis, design of surveys and experiments, introduction
to estimation and significance tests and the use of statistics in the social
sciences and the media. (M) |
| STA 4033 Mathematical Statistics with Computer Applications.
F, S. |
| Credits: 2 |
Prereq: STA 3023 or STA 3032, MAC 2312, CIS 3020 or equivalent. |
| Computer simulations on simple statistical techniques such
as histograms, z-tests and t-tests; analyzing large data sets by regression,
contingency tables, non-parametric and simple multivariate procedures.
(M) |
| STA 4170 Introduction to Statistical Methods in Pharmacy.
S. |
| Credits: 3 |
Prereq: |
| Introduces statistical design and analysis techniques needed
to perform pharmaceutical research and evaluate articles in the medical
literature. Designing epidemiologic and clinical studies, evaluating diagnostic
testing procedures, interpreting the use of rates in medical literature,
and using frequently used statistical methods of data analysis. Emphasis
will be on concepts and their application to critical appraisal of statistical
contents in medical literature. (M) |
| STA 4173 Biometry. F (odd number years). |
| Credits: 3 |
Prereq: STA 4210 or STA 4322 or equivalent. |
| Specialized statistical methods in the medical sciences.
Contents include analysis of rates and proportions, analysis of survival
data, dose response curves, study designs and binary regression. (M) |
| STA 4210 Regression Analysis. F, S. |
| Credits: 3 |
Prereq: STA 3023 or STA 3032 or STA 4322. |
| Simple linear regression and multiple linear regression
models. Inference about model parameters and predictions, diagnostic and
remedial measures about the model, independent variable selection, multicolinearity,
autocorrelation, and nonlinear regression. SAS implementation of the above
topics. (M) |
| STA 4211 Design of Experiments. S. |
| Credits: 3 |
Prereq: STA 4210. |
| An introduction to the basic principles of experimental
design: analysis of variance for experiments with a single factor; randomized
blocks and Latin square designs: multiple comparison of treatment means;
factorial and nested designs; analysis of covariance; an introduction to
response surface methodology. (M) |
| STA 4222 Sample Survey Design. F (even number years). |
| Credits: 3 |
Prereq: STA 3023 or STA 3122 or STA 4322. |
| An introduction to the design of sample surveys and the
analysis of survey data, the course emphasizes practical applications of
survey methodology. Topics include sources of errors in surveys, questionnaire
construction, simple random, stratified, systematic and cluster sampling,
ratio and regression estimation, and a selection of special topics such
as applications to quality control and environmental science. (M) |
| STA 4321 Mathematical Statistics 1. F, S, SS. |
| Credits: 3 |
Prereq: MAC 2313 or equivalent. |
| Introduction to the theory of probability, counting rules,
conditional probability, independence, additive and multipicative laws,
Bayes Rule. Discrete and continuous random variables, their distributions,
moments, moment generating functions. Multivariate probability distributions,
independence, covariance. Distributions of functions of random variables.
(M) |
| STA 4322 Mathematical Statistics 2. F, S, SS. |
| Credits: 3 |
Prereq: STA 4321 or equivalent. |
| Sampling distributions, central limit theorem, estimation,
properties of point estimators, confidence intervals, hypothesis testing,
common large sample tests, normal theory small sample tests, uniformly
most powerful and likelihood ratio tests, linear models and least squares,
correlation. Introduction to analysis of variance. (M) |
| STA 4502 Nonparametric Statistical Methods. F. |
| Credits: 3 |
Prereq: STA 3023 or STA 3032 or STA 4210 or STA 4322. |
| Introduction to nonparametric statistics, including one
and two sample testing and estimation methods, one and two way layout models
and correlation and regression models. (M)
|
| STA 4504 Categorical Data Analysis. S. |
| Credits: 3 |
Prereq: STA 3023 or STA 3032 or STA 4210 or STA 4322. |
| Description and inference using proportions and odds ratios, multi-way contingency tables, logistic regression and other generalized linear models, loglinear models applications. (M)
|
| STA 4664 Industrial Statistics. S (even number years). |
| Credits: 3 |
Prereq: STA 3032 or a 4000 or higher level STA course. |
| Philosophy and tools of total quality management, design
of experiments for process optimization via response surface methods including
factorial, fractional factorial, Plackett-Burman and central composite
designs; control chart methods,including Shewhart and cusum charts. (M)
|
| STA 4702 Multivariate Statistical Methods. S (odd number years). |
| Credits: 3 |
Prereq: STA 3024 or STA 4322 or STA 6127 or STA 6167 or STA 4211 |
| Review of matrix theory, univariate normal, t, chi-squared, F and multivariate normal distributions. Inference about multivariate means including Hotelling's T squared, multivariate analysis of variance, multivariate regression and multivariate repeated measures. Inference about covariance structure including principal components, factor analysis and cannonical correlation. Multivariate classification techniques including discriminant and cluster analyses. Additional topics at the discretion of the instructor, time permitting. |
| STA 4821 Stochastic Processes. |
| Credits: 3 |
Prereq: STA 4321 or equivalent. |
| Theoretical development of elementary stochastic processes, including Poisson processes and their generalizatons, Markov chains, birth and death processes, branching processes, renewal processes, queueing processes and genetic and ecological processes. |
| STA 4853 Introduction to Time Series and Forecasting. S |
| Credits: 3 |
Prereq: STA 4322 or equivalent. |
| Stationarity, autocorrelation, ARMA models. Frequency domain methods, the spectral density. Forecasting methods. Computationally-oriented, applications to case studies. |
| STA 4905 Individual Work. F, S, SS. |
| Credits: 1 to 5 |
Prereq: permission of department. |
| Special topics designed to meet the needs and interests
of individual students. May be repeated with change of content up to a
maximum of 15 credits |
| STA 4930 Special Topics. |
| Credits: 3 |
Prereq: Permission of the department chairman. |
| Rotating topics designed to meet the needs and interests
of individual students. May be repeated with change of content up to a
maximum of 15 credits. |
| MAC 2312 Analytic Geometry & Calculus 2. F, S, SS.
|
| Credits: 4 |
Prereq: MAC 2311 or MAC 3472. |
| Techniques of integration; applications of integration;
differentiation and integration of inverse trigonometric, exponential and
logarithmic functions; sequences and series. (M) |
| MAC 2313 Analytic Geometry & Calculus 3. F, S, SS.
|
| Credits: 4 |
Prereq: MAC 2312 or MAC 3512 or MAC 3473. |
| Solid analytic geometry; vectors; partial derivatives;
multiple integrals. (M) |
| MAS 2103 Matrices and Vector Spaces. F, S. |
| Credits: 3 |
Prereq: MAC 2311 or MAC 3472 or MAC 2233. |
| Linear equations and matrices, elementary determinants,
linear geometry of Euclidean spaces, vector spaces and linear transformations,
eigenvalues. (M) |
| MAS 3114 Computational Linear Algebra. F, S, SS. |
| Credits: 3 |
Prereq: MAC 2312 (or MAC 3512 or MAC 3473) and a scientific programming
language. |
| Linear equations, matrices and determinants. Vector spaces
and linear transformations. Inner products and eigenvalues. This course
emphasizes computational aspects of linear algebra. (M) |
| MAS 4105 Linear Algebra 1. F, S, SS. |
| Credits: 4 |
Prereq: MAC 2313 or MAC 3474; MAS 3300 recommended. |
| Linear equations, matrices, vector spaces, linear transformations,
determinants, eigenvalues, inner product spaces. |
| CIS 3020 Introduction to CIS. |
| Credits: 3 |
Prereq: MAC 2311 or MAC 2233. |
| Introduction to computers and algorithms. Programming
in a high level language. Topics include procedural abstraction, data abstraction,
and structured programming techniques. The student will learn the fundamentals
of developing coherent, expressive programs. |
| CGS 2420 Computer Programming Using FORTRAN. F.
|
| Credits: 3 |
Prereq: MAC 1142 or equivalent. |
| An indepth treatment of computer programming using FORTRAN.
Problems related to a variety of disciplines are solved. An introduction
to the basic concepts of software and hardware is provided. This course
cannot be used for credit toward a CISE degree program. (M) |
| CGS 2425-25L Computer Programming for Engineers. |
| Credits: 2 |
Prereq: MAC 2312. |
| Computer programming and the use of computers to solve
engineering and mathematical problems. Emphasis will be placed on applying
problem solving skills. This intensive course is specifically directed
towards those students who are pursuing technical careers in fields employing
a reasonably high degree of mathematics. The programming language used
will depend on the demands of the departments in the college. In one semester,
several languages may be taught, no more than one per section. If you are
required to learn a specific language, be sure to enroll in the correct
section. |
| CGS 2425L Computer Programming for Engineers Laboratory.
|
| Credits: 1 |
Coreq: CGS 2425. |
| Optional laboratory course in conjunction with CGS 2425.
Engineering: Industrial |
| CGS 3403 Computer Programming Using COBOL. |
| Credits: 3 |
Prereq: none |
| A course in COBOL programming for non-CISE majors. Structured programming in COBOL is stressed. Topics include data transfer, arithmetic and logical operations, the structuring of data, and arrays. (M) |
| CGS 3460 Computer Programming Using C. |
| Credits: 3 |
Prereq: MAC 1142 or equivalent. |
| An indepth treatment of computer programming using C. Problems
related to a variety of disciplines are solved. An introduction to the
basic concepts of software and hardware is provided. This course cannot
be used for credit toward a CISE degree program. (M) |
| CGS 3462 Computer Programming Using Pascal. F, S.
|
| Credits: 3 |
Prereq: Knowledge of college algebra. |
| An indepth treatment of computer programming using Pascal.
Problems related to a variety of disciplines are solved. An introduction
to the basic concepts of software and hardware is provided. This course
cannot be used for credit toward a CISE degree program. (M) |
| COT 4501 Numerical AnalysisÐA Computational Approach.
F, S, SS. |
| Credits: 3 |
Prereq: CIS 3020 and MAS 3114. |
| Numerical integration, nonlinear equations, linear and
nonlinear systems of equations, differential equations and interpolation.
Computer & Information Systems |
| ESI 4312 Operations Research 1. |
| Credits: 3 |
Prereq: CGS 3422, ESI 4567. |
| Classical optimization; methods of Lagrange multipliers;
Kuhn-Tucker conditions. Linear programming; simplex algorithm, sensitivity
analysis; duality. Transportation and assignment problems; network flows.
Integer programming. Applications. |
| MAA 4102 Introduction to Advanced Calculus for Engineers
and Physical Scientists 1. F, S. |
| Credits: 3 |
Prereq: MAC 3313 or MAC 3474 and grade of C or better in MAS 4105 or
MAS 3114. |
| Review of limits, differentiation, and integration; calculus
of vector functions; line and surface integration; calculus of variations;
Fourier series. Material presented with view to applications. |
| MAA 4211 Advanced Calculus 1. F. |
| Credits: 3 |
Prereq: grade of C or better in MAS 4105. |
| An advanced treatment of limits, differentiation, integration,
series; calculus of functions of several variables. |
| MAD 4401 Introduction to Numerical Analysis. F, S. |
| Credits: 3 |
Prereq: MAS 4105 or MAS 3114 and a scientific programming language.
|
| Numeric integration, nonlinear equations, linear and non-linear
systems of equations, differential equations and interpolation. |
| MAS 4105 Linear Algebra 1. F, S, SS. |
| Credits: 4 |
Prereq: MAC 3313 or MAC 3474; MAS 3300 recommended. |
| Linear equations, matrices, vector spaces, linear transformations,
determinants, eigenvalues, inner product spaces. |
| MAS 4107 Linear Algebra 2. S. |
| Credits: 3 |
Prereq: MAS 4105. |
| Further topics in linear algebra. |
NOTE: A Schedule
of Courses is also kept by the Office
of the University Registrar.
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Last modified: Thu Oct 7 10:14:56 EDT 2004