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College of Engineering & Science - Louisiana Tech University


Computational Analysis & Modeling

Applied Statistics & Knowledge Discovery

Steering Committee Coordinator: Please contact Dr. Mihaela Paun (mpaun@LaTech.edu) or Dr. Jim Cochran (jcochran@LaTech.edu) regarding any questions about the Applied Statistics track in CAM.

Math Core (9 SCH): (Common to all Tracks)
MATH 414 & MATH 415 with either MATH 407 or STAT 620/STAT 621

Math 407 (Partial Differential Equations)
3 Credit Hours. Preq, MATH 245, Solution of linear first order equations. Formation and solution of second order problems of parabolic, elliptic, and hyperbolic type. (G)

Math 414 (Numerical Analysis)
3 Credit Hours. Preq, MATH 245, knowledge of a programming language. Roots of polynomial and other nonlinear equations. Interpolating polynomials. Numerical differentiation. Numerical Integration. Direct methods for solving linear systems.(G)

Math 415 (Numerical Analysis)
3 Credit Hours. Preq, MATH 245, knowledge of a programming language. Numerical applications of linear algebra. Curve fitting. Function approximation. Numerical solution of systems of equations, differential equations, systems of differential equations, boundary value problems. (G)

STAT 620 (Theory of Probability)
3 Credit Hours. Preq, any 500 level STAT Course, and MATH 244. Combinatorial analysis, conditional probability, distribution theory, random variables, random vectors, limit theorems and random walks.

STAT 621 (Theory of Statistics)
3 Credit Hours. Preq, STAT 520 or 620. Point estimation, interval estimation, statistical hypothesis, statistical tests, non parametric inference, and normal distribution theory.

CS Core (6 SCH): (Common to all Tracks)
CSC 428 & CSC 438

CSC 428 (Object Oriented Programming and Data Structures)
3 Credit Hours. Preq, consent of instructor. Programming paradigms, syntax, semantics, data types, expression, control statements and sub programs; object oriented concepts, abstract data types, recursion, queues and trees. (G)

CSC 438 (Special Topics in Software Development)
3 Credit Hours. Preq, consent of instructor. Selected topics in the area of software design that are of current importance or special interest. (G) 

Supporting Core (CS - 3 SCH, MATH - 6SCH)
CSC 579, STAT 506 or QA 602, STAT 511 or QA 605

CSC 579 (Data Mining and Knowledge Discovery)
3 Credit Hours. Preq, CSC325/equivalent OR consent of instructor. Topics include: Introduction to Data Mining (DM), Knowledge Discovery in large databases, Data preprocessing and normalization, Dimensionality reduction, DM primitives, Mining frequent itemsets in large DBMS, Association rule mining, Classification and evaluation measures.

STAT 506 (Regression Analysis)
3 Credit Hours. Preq, STAT 405 or equivalent. Simple and multiple regressions, inferences in regression, model formulation and diagnostics, analysis of covariance, non linear models, estimation and inference. Use of computers in data analysis.

STAT 511 (Design of Experiments)
3 Credit Hours. Preq, STAT 506 OR 507 or 508 or equivalent. Factorial and fractional factorial experiments, incomplete block designs, repeated measures, split-plot, response surface, cross-over designs, and use of computers for data analysis.

QA 605 (Methods of Business Research)
3 Credit Hours. Preq, QA 522 or consent of instructor. Formulation of statistical hypotheses germane to business research. Determination of the experimental conditions and extraneous conditions. Methods of measurement and the statistical analysis required.

QA 622 (Advanced Business Statistics)
3 Credit Hours. Preq, QA 432. Requires Doctoral standing. May require additional class meetings. Applied statistical methods utilizing the computerized Statistical Analysis System (SAS).

Suggested Elective Courses (21 SCH total)
(see advisor)
STAT 625 or QA 610, STAT 507, STAT 652, STAT 650, STAT 680, CAM 657

STAT 625 (Multivariate Statistics)
3 Credit Hours. Preq, STAT 506 OR 507 or 508 or equivalent. Test of hypotheses on means, multivariate analysis of variance, canonical correlation, principal components, factor analysis, and computer applications.

QA 610 (Multivariate Statistics: Business Applications)
3 Credit Hours. Preq, QA 522. Regression extensions, canonical correlation, multivariate ANOVA, discriminant, business applications, principal components using SAS, SPSS, and BMD, factor and cluster analysis.

STAT 507 (Analysis of Variance)
3 Credit Hours. Preq, STAT 405 or equivalent. Analysis of variance for standard and unbalanced experimental designs, multiple comparisons, fixed random and mixed effects models. Use of computers for data analysis.

STAT 650 (Time Series Analysis)
3 Credit Hours. Preq, MATH 244 and STAT 506. Spectral Analysis, least square filtering, parameter estimation, stationary random processes, ARIMA models, trend and seasonability.

STAT 652 (Stochastic Process)
3 Credit Hours. Preq, MATH 244 and 308 and STAT 520. Probability generating functions, Markov chains, renewal processes, Poisson processes, branching processes

STAT 680 (Topics in Statistics)
3 Credit Hours (9). May be repeated for 3 hours credit each time.

Directed Study (6 SCH)

CAM 650 or equivalent courses with other prefixes.

Qualifying Exam

MATH: CAM 685

CS: CAM 686

Dissertation (18 SCH)

CAM 651

Total (72 SCH)= MATH 15SCH + CS 9SCH + Elective 21 SCH + Directed Study 6 SCH + CAM610 3SCH + Dissertation 18 SCH.