Department of Mathematics and Statistics

This is an archived copy of the 2022-2023 catalog. To access the most recent version of the catalog, please visit http://catalog.shsu.edu.

Chair: Dr. Paul Jung(936) 294-4859

Contact Information: (936) 294-1564

Website: Department of Mathematics and Statistics
 

Mission

The Department of Mathematics and Statistics will provide all students with the opportunity to receive an educational experience in mathematics and statistics of the highest quality, both inside and outside the classroom. By actively engaging in research and professional development, the faculty will promote quality scholarship among themselves as well as their students.

Highlights

  • Opportunities for research through numerous grants with industry, government and education agencies
  • Support for travel and presentations at local and national professional meetings
  • Opportunities for discipline-related employment, including classroom teaching, grading and tutoring

Career Opportunities

  • Accounting and Finance
  • Computer Programming
  • Data Science
  • Sales and Marketing
  • Management and Related Positions
  • Actuarial Science
  • Computer Systems Analysis
  • Engineering
  • Statistics
  • Mathematics
  • Operations Research
  • Modeling
  • Academic Positions - High School or College

Student Organizations

  • American Mathematical Society (AMS) Student Chapter
  • Mathematical Association of America (MAA)
  • Pi-Mu-Epsilon Mathematics Honor Society
  • Stat Club 

Assistantships

The Department of Mathematics and Statistics offers a significant number of graduate teaching assistantships each year. For more information, call (936) 294-1564.

Scholarships

The Department of Mathematics and Statistics offers several scholarships each year and Sam Houston State University offers additional, university-wide scholarships. For information on departmental scholarships, visit the departmental website. Information on University scholarships may be obtained from the Financial Aid and Scholarships Office.

Mathematics

MATH 5360. Special Topics. 3 Hours.

Topics and courses are selected to suit individual needs of students. Methods of independent study and research are stressed. The course may be repeated for additional credit.
Prerequisite: Consent of program coordinator.

MATH 5361. Theory & App Of Probability. 3 Hours.

Topics include probability axioms and properties, conditional probability, random variables, probability distributions, moment generating functions, laws of large numbers, and the Central Limit Theorem. Also listed as STAT 5361.
Prerequisite: STAT 4372 (or equivalent) or consent of the instructor.

MATH 5365. Introductory Analysis. 3 Hours.

Students engage in a more thorough treatment of the material traditionally considered in elementary calculus. Topics may include sets, functions, properties of the real number system and sequences. NOTE: Students who have taken Math 4361 may not take MATH 5365.
Prerequisite: Graduate Standing.

MATH 5366. Elementary Analysis. 3 Hours.

Students study limits, continuity, differentiation, Riemann integration, infinite series and sequences, and series of functions. NOTE: Students who have taken Math 4366 may not take MATH 5366.
Prerequisite: Graduate Standing and MATH 4365 or MATH 5365.

MATH 5370. Fourier Analysis & Application. 3 Hours.

This course is a study of applied harmonic analysis. Topics include Fourier analysis, wavelet analysis, and applications of these topics.
Prerequisite: MATH 4366 or MATH 5388 or the consent of the instructor.

MATH 5375. Partial Differential Equations. 3 Hours.

Students solve problems involving partial differential equations from the natural sciences. Topics may include derivation of the heat/diffusion and wave equations, the method of separation of variables to solve the heat, wave, and Laplace equations on finite domains, Fourier series, Sturm-Liouville eigenvalue problems, the Fourier transform method to solve equations on infinite domains, the method of characteristics, and d'Alembert's solution of the wave equation. NOTE: Students who have taken MATH 4375 may not take MATH 5375.
Prerequisite: Graduate Standing.

MATH 5377. Algebraic Structures. 3 Hours.

Students study basic structures of abstract algebra: groups, rings, and fields. Topics may include elementary number theory, equivalence relations, groups, homomorphisms, cosets, Cayley's Theorem, symmetric groups, rings, polynomial rings, quotient fields, principal ideal domains, and Euclidean domains. Note: Students who have taken Math 4377 may not take MATH 5377.
Prerequisite: Graduate Standing.

MATH 5380. Research Project In Math Edu. 3 Hours.

In this course, the student will develop a project based on one of the core areas (Algebra, Geometry, Analysis, or Probability and Statistics) appropriate for use in teaching. This course is a capstone for candidates pursuing the degree of MA of Mathematics.
Prerequisite: MATH 5386, MATH 5387, MATH 5388, MATH 5389.

MATH 5381. Algebra:Structr & Applications. 3 Hours.

This course includes the study of algebraic structures (such as groups, rings, integral domains, and fields) and their properties, and activities and concepts related to the algebra of real numbers that are applicable to middle school teachers. The course is designed for in-service middle school mathematics teachers.

MATH 5382. Discrete Math for Teachers. 3 Hours.

This course will include a study of graph theory, combinatorics and recursion, social choice and apportionment, algorithms, and iteration, with an emphasis on real-world problem solving applications and mathematical connections to the school curriculum. This course is specifically designed for middle and high school teachers, with a mathematics specialization, obtaining a Master's Degree in Education with a minor in mathematics.
Prerequisite: Middle or secondary school mathematics certification, or equivalent.

MATH 5383. Seminar in Geometry and Measurement for Teachers. 3 Hours.

This course will include a study of congruency, similarity, transformations, coordinate geometry, and measurement. It is specifically designed for teachers with a mathematics specialization who wish to obtain the master's degree in education with a minor in mathematics.
Prerequisite: Middle school mathematics certification and MATH 3383 or equivalent.

MATH 5384. Sem in Math Sys for Teachers. 3 Hours.

This course will include a study of the development of the natural number system, the development of the integers, the development of the rational number system, and the development of the real number system. It is specifically designed for teachers with a mathematics specialization who wish to obtain the master's degree in education with a minor in mathematics.
Prerequisite: Middle school mathematics certification and MATH 3384 or equivalent.

MATH 5385. Sem Num Theory&Prop for Teach. 3 Hours.

This course includes topics from arithmetic, algebra, geometry, number theory and other mathematical areas at a level appropriate for junior high school teachers.
Prerequisite: Consent of instructor.

MATH 5386. Concepts in Modern Algebra. 3 Hours.

This course consists of a survey of several abstract algebraic systems including groups, rings, integral domains, and fields.
Prerequisite: Certification in secondary school mathematics and MATH 3377 or equivalent.

MATH 5387. Transformational Geometry. 3 Hours.

This course is a study of topics in geometry including constructions and transformations.
Prerequisite: Certification in secondary school mathematics and MATH 3363 or equivalent.

MATH 5388. Concepts in Analysis. 3 Hours.

This course includes topics from set theory, number systems, functions, real sequences, limits, continuity, differentiation and integration.
Prerequisite: Certification in secondary school mathematics and MATH 1430 or equivalent.

MATH 5389. Concepts in Probability & Stat. 3 Hours.

This course includes topics from probability theory, distribution functions, descriptive statistics, and inferential statistics.
Prerequisite: Certification in middle or secondary school mathematics and MATH 3379 or equivalent.

MATH 5395. Digital Image Processing. 3 Hours.

The emphasis of this course is on the analysis of digital image processing algorithms used for solving problems in areas such as image enhancement and restoration, image registration, pattern recognition, and image segmentation.
Prerequisite: MATH 3377 and programming experience.

MATH 5396. Optimization. 3 Hours.

The emphasis of this course is on modern algorithms and computational methods needed for solving optimization problems. Applications to current industrial problems will be given, and the theory of operations research will be developed.
Prerequisite: MATH 3377 and MATH 2440, or consent of instructor.

MATH 5397. Discrete Mathematics. 3 Hours.

Discrete structures are emphasized in this course, which includes a study of combinatorics, graph theory, and number theory. The applications of these structures in computers and communications will be highlighted.
Prerequisite: MATH 4377 or MATH 5386 or equivalent.

MATH 6060. Independent Study. 1-3 Hours.

Students independently pursue a specific topic in advanced mathematics under a faculty member's supervision. The problems addressed in the course will be mutually selected and approved by the student and a mathematics faculty member. A thorough development of necessary axioms, definitions and properties from any related coursework will be reviewed before students are guided to extend those elements towards the main results from the chosen topic. These results may be practical applications of prior coursework and/or theoretical foundations of an advanced topic, specific to the students' individual needs and goal. Variable Credit (1 to 3).
Prerequisite: Consent of instructor.

MATH 6099. Research and Thesis. 1-3 Hours.

MATH 6332. Introduction To Topology. 3 Hours.

This course is a rigorous introduction to point set topology. Topics include continuity, connectedness, compactness, metrization theorems, separation theorems, and the Tychonoff theorem.
Prerequisite: MATH 3300 or equivalent.

MATH 6333. Foundations Of Analysis I. 3 Hours.

This course is the first half of the analysis sequence. The analysis sequence includes topics from advanced multivariate calculus, normed linear spaces, measure theory, including Lebesgue and Borel measures, measurable functions, Lebesgue integration, and spaces of integrable functions.
Prerequisite: MATH 4361 and MATH 4366, equivalent, or consent of instructor.

MATH 6334. Foundations Of Analysis II. 3 Hours.

This course is the second half of the analysis sequence. The analysis sequence includes topics from advanced multivariate calculus, normed linear spaces, measure theory, including Lebesgue and Borel measures, measurable functions, Lebesgue integration, and spaces of integrable functions.
Prerequisite: MATH 6333 or consent of instructor.

MATH 6335. Algebra I. 3 Hours.

This course is in the first half of the algebra sequence. The algebra sequence will include Group and Ring theory. Special topics include groups, group actions, the Sylow Theorems, rings, modules, fields, field extensions, and an introduction to Galois Theory.
Prerequisite: MATH 4377 or equivalent.

MATH 6336. Algebra II. 3 Hours.

This course is the second half of the algebra sequence. The algebra sequence will include Group and Ring theory. Specific topics include groups, group actions, the Sylow Theorems, rings, modules, fields, field extensions, and an introduction to Galois Theory.
Prerequisite: MATH 6335 (Algebra I) or equivalent.

MATH 6340. Algebraic Geometry. 3 Hours.

This course will provide an introduction to algebraic geometry emphasizing both classical theory and the practical aspects of computations with polynomial ideals using Groebner bases. Topics include Groebner bases, affine varieties, morphisms and rational maps, elimination theory, the Nullstellensatz, primary decomposition, projective varieties, Grassmannians, and Hilbert Functions.
Prerequisite: Math 6336.

MATH 6342. Algebraic Topology. 3 Hours.

An introduction to the concepts of homotopy and homology theories. The following topics will be included: The fundamental group, classification of surfaces, higher homotopy groups, cellular and/or simplicial homology.
Prerequisite: MATH 6332.

MATH 6352. Differential Geometry. 3 Hours.

This course examines the local and global geometric and topological properties of curves and surfaces in 3-dimensional Euclidean space. Topics will include curvature and torsion of space curves, mean and Guassian curvature of surfaces, and the Gauss-Bonnet theorem. In addition, the course will also examine smooth Riemannian manifolds, the curvature tensor, geodesics, and applications such as surfaces of constant mean curvature.

MATH 6360. Special Topics In Mathematics. 3 Hours.

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MATH 6361. Mathematical Logic. 3 Hours.

Students examine logical metatheory and meta-mathematics, which is the field at the intersection of mathematics and logic that investigates logical reasoning with mathematical methods. Topics include completeness and soundness proofs for first-order predicate logic and its extensions, the formal theory of deduction, and fundamental Gödel completeness theorem and related results. The compactness theorem is established, coordinating semantics and deduction, meaning, and consequence.
Prerequisite: MATH 3300.

MATH 6367. History of Adv Mathematics. 3 Hours.

This course examines the history of the development of modern mathematics, from the discovery of calculus, through the industrial revolution, into the modern age of computers and digital technology. Emphasis will be placed on the applications of calculus and the abstraction of geometry, analysis, and algebra which followed.
Prerequisite: Math 4367 or departmental approval.

MATH 6368. Numerical Linear Algebra. 3 Hours.

This course is a study of vector spaces and matrices. Topics include solving linear systems, least square methods, eigenvalue and eigenvector theory, and applications of these topics.
Prerequisite: MATH 3377 or consent of instructor.

MATH 6373. Applied Analysis. 3 Hours.

This course studies properties of normed spaces and functions defined on normed spaces. Special emphasis is placed on Euclidean n-space. Topics include limits, continuity, differentiation, and integration.
Prerequisite: MATH 4366 or MATH 5388 or consent of the instructor.

MATH 6376. Foundations of Applied Math. 3 Hours.

This course provides a comprehensive presentation of the standard methods of applied mathematics that are used when solving problems posed in engineering and science. Topics may include finite dimensional vector spaces, function spaces, integral equations, differential operators, calculus of variations, complex variable theory, transform and spectral theory, ordinary and partial differential equations, bifurcation theory, nonlinear waves, and asymptotic expansions, and perturbation theory.
Prerequisite: MATH 3376 and MATH 3377 or their equivalents.

MATH 6377. Abstract Algebra. 3 Hours.

Algebraic structure is emphasized in this course, which includes a study of groups, rings, fields, and their applications in coding theory and cryptography.
Prerequisite: MATH 4377 or MATH 5386 or consent of instructor.

MATH 6379. Functions Of Complex Variable. 3 Hours.

Included in this course are studies of the complex number system, analytic functions, integration theory and the calculus of residues. Additional topics of special interest to the class may be included.
Prerequisite: MATH 2440 or consent of instructor.

MATH 6380. Research Methods in Mathematics. 3 Hours.

Students work on a specific research topic under a faculty member's supervision. The specific topic will be chosen from current trends and future directions of an active field of mathematics. The course content will vary based upon the topic the student and the mentoring faculty member choose. Regular meetings with other students in the course will focus on expected elements of the research paper and presentation that are required for successful completion of the course.
Prerequisite: Consent of instructor.

MATH 6381. Connections: Algebra, Trigonometry, Combinatorics. 3 Hours.

Students examine topics that span the fields of algebra of polynomials, complex numbers, trigonometry, and combinatorics. The course goal is to develop an in-depth understanding of the connections among these branches of mathematics, and how knowledge of one branch applies in the others.

MATH 6382. Issues in Undergraduate Math Education. 3 Hours.

Students study pedagogical issues related to undergraduate mathematics education. Topics may include national and Texas perspectives on pedagogical issues with respect to undergraduate mathematics education, designing an effective mathematics course and class (in face-to-face, online, and hybrid platforms), establishing a productive mathematics learning environment, using active learning techniques, promoting higher-order thinking, and assessing to inform instruction and promote learning.

MATH 6385. Advanced Mathematical Problem Solving. 3 Hours.

Students study advanced mathematical problem-solving processes and strategies and practice their learning by solving real-world problems to prepare them for their individualized end-of-program capstone research projects. Students will explore how to design, conduct, carry out, and report on a problem-solving project in a selected content area. Topics may include advanced concepts in algebra, geometry, financial mathematics, and calculus, including functions, graphs, complex numbers, and number systems.
Prerequisite: Graduate Standing.

MATH 6386. Number Theory. 3 Hours.

Students examine elementary properties of the ring of integers. Topics include concepts, algorithms, and proofs of fundamental results of modular arithmetic, the distribution of prime numbers, unique factoring, and modern applications of these ideas.
Prerequisite: Graduate Standing.

MATH 6387. Concepts in Linear Algebra. 3 Hours.

Students learn advanced topics in Linear Algebra with an emphasis on abstract vector spaces and proof. Topics include vector spaces, linear maps, eigenvalues, eigenvectors, invariant subspaces, inner product spaces, and complex vector spaces.
Prerequisite: MATH 3377, or equivalent.

MATH 6394. Scientific Computation. 3 Hours.

Topics include solutions of equations, approximation and interpolation, numerical differentiation and integration, the fast Fourier transform, and numerical simulation. Also listed as COSC 6321.
Prerequisite: MATH 2440 and some programming experience, or consent of instructor.

MATH 6398. Research And Thesis. 3 Hours.

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Statistics

STAT 5111. Software For Stat Sciences. 1 Hour.

Topics include MINITAB, SAS, Maple and Scientific Workplace (or equivalents). This one-hour course is available for graduate students in all disciplines.
Prerequisite: STAT 3380 (or equivalent), graduate standing, and consent of instructor.

STAT 5333. Dsgn & Anal Of Experiments. 3 Hours.

Topics include the design, analysis and interpretation of results from standard experimental design models including the completely randomized design, the randomized complete block, the incomplete block, factorial models, Latin squares, Greco-Latin squares, screening designs, fractional factorials, and general fixed, mixed and random effects ANOVA models.
Prerequisite: STAT 4372 (or equivalent).

STAT 5360. Special Topics In Statistics. 3 Hours.

Topics are selected from emerging areas in statistics that are not covered in regular courses. Such topics as data mining, statistical learning, pattern recognition, spatial statistics, statistical methods in finance, functional data analysis, life contingencies may be included. Also listed as MATH 5360.
Prerequisite: Consent of instructor.

STAT 5361. Thry & Appltn Of Probability. 3 Hours.

Topics include probability axioms and properties, conditional probability, random variables, probability distributions, moment generating functions, laws of large numbers and the Central Limit Theorem. Also listed as MATH 5361.
Prerequisite: STAT 4372 (or equivalent) or consent of instructor.

STAT 5362. Thry & Appltn Of Statistics. 3 Hours.

Topics include convergence in probability and distribution, point estimation, hypothesis testing, interval estimation, maximum likelihood methods, properties of estimators such as efficiency, sufficiency and completeness, exponential family of distributions, most powerful tests, uniformly most powerful tests, and likelihood ratio tests.
Prerequisite: STAT 5361 (or equivalent) or consent of instructor.

STAT 5364. Applied Multi Statistical Anal. 3 Hours.

Topics include the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, principal components analysis, clustering, discriminant and classification analysis.
Prerequisite: STAT 4372 (or equivalent) or consent of instructor.

STAT 5365. Linear Statistical Models. 3 Hours.

Topics include the statistical properties of quadratic forms, the full-rank general linear statistical model, the less-than-full-rank model, the linear model structure of regression models, ANOVA models, ANCOVA models, the general characteristics of the fixed, mixed and random effects models and model diagnostics considerations.
Prerequisite: STAT 4372 or STAT 5362 (or equivalents).

STAT 5366. Sampling Methods. 3 Hours.

Topics include the theory and applications of standard methods for performing scientific-based sampling. Among these are simple random sampling, cluster sampling, stratified random sampling, systematic sampling, probability proportional to size (pps) sampling, sampling from finite populations and ratio regression estimation.
Prerequisite: STAT 4372, STAT 5362, or consent of instructor.

STAT 5367. Reliability Anal & Qual Ctrl. 3 Hours.

Topics include measures of failure, reliability functions, failure models, life testing and censoring, system reliability, parameter estimation and testing, control charting, acceptance sampling plans, software reliability and process control.
Prerequisite: STAT 4372, STAT 5362, or consent of instructor.

STAT 5368. Regression Modeling & Analysis. 3 Hours.

Topics include model estimation and testing, simple and multiple regression models, residual analysis, variables selection, polynomial regression, multicollinearity, ridge regression, logistic regression and real data analysis and applications.
Prerequisite: STAT 4372, STAT 5362, or consent of instructor.

STAT 5369. Stat Computing & Consulting. 3 Hours.

This course consists of a detailed study of the SAS package including SAS/BASICS, SAS/STAT, SAS/GRAPH and SAS/IML with emphasis on applying these tools in a consulting environment. Techniques and principles important in working with representatives of user disciplines are included.
Prerequisite: STAT 3380 and graduate standing.

STAT 5370. Nonparametric Statistics. 3 Hours.

Topics include order statistics, contingency analysis, rank tests (Wilcoxin signed-rank test, Mann-Whitney U test and others), distribution-free tests of location and scale, nonparametric regression, Kendall's tau and related areas.
Prerequisite: STAT 4372 (or equivalent) or consent of instructor.

STAT 5375. Statistical Methods for Agriculture. 3 Hours.

This course explores applications of statistical methods for making interpretations of qualitative and quantitative data in agricultural research. Topics include sampling and randomization, correlation and regression, methods of inference for means and proportions, and design of experiments.

STAT 6060. Independent Study. 1-3 Hours.

Students research a subject in depth under the direct supervision of a faculty member with expertise in the particular area of study. The topic of study will be mutually selected and approved by the student and Statistics faculty member. Variable Credit (1 to 3).
Prerequisite: Consent of instructor.

STAT 6099. Research and Thesis. 1-3 Hours.

This course continues the thesis research and concludes with a carefully written solution of the thesis problem and a satisfactory oral presentation of the results. Study must be supervised by a member of the graduate statistics faculty. Variable Credit (1-3).
Prerequisite: STAT 6398.

STAT 6366. Applied Bayesian Analysis. 3 Hours.

This course presents Bayesian methods and their application to fields such as agriculture, biology, criminal justice and medicine. Topics include basic models that use the binomial, normal, poisson and gamma distributions; complex models that apply Markov Chain Monte Carlo methods like the Gibbs sampler and the Metropolis-Hastings algorithm; model selection and evaluation of model adequacy. Software current to the discipline will be used to analyze data.
Prerequisite: STAT 4372 or departmental approval.

STAT 6375. Biostatistics. 3 Hours.

This course consists of the topics related to statistical methods in biomedical studies: Types of biomedical study designs, assessment of risk factors, measure of disease-exposure association, logistic regression, analysis of count data, analysis of event-time data, and resampling methods.
Prerequisite: STAT 4372 or departmental approval.

STAT 6376. Time Series Analysis. 3 Hours.

This course presents both classical and modern approaches to time series analysis. Topics include autoregressive integrated moving average models, exponential smoothing models, and time series regression methods. Emphasis is placed on building time series models for forecasting.
Prerequisite: STAT 4372 or departmental approval.

STAT 6377. Intro. To Survival Analysis. 3 Hours.

Students explore both the theory and real-world applications of survival analysis in the biomedical and engineering fields. Topics may include nonparametric, semiparametric, and parametric survival methods, model diagnostics, and modern techniques for survival analysis methods. Statistical software such as SAS and R will be used to analyze data.
Prerequisite: STAT 5361 or approval of the instructor.

STAT 6378. Longitudinal Data Analysis. 3 Hours.

Students explore the statistical analysis of longitudinal data. This course focuses on modern statistical methods for longitudinal data and their applications in real world problems. Topics may include repeated measures, modeling longitudinal data, analysis of variance in repeated measures, population averaged models, linear mixed effect models, generalized estimating equations, and generalized linear mixed effect models. Statistical software such as SAS and R will be used extensively to analyze data.
Prerequisite: STAT 4372 (or equivalent) or approval of the instructor.

STAT 6380. Statistics Practicum. 3 Hours.

Students work on a specific research topic under a faculty member's supervision. The specific topic or problem will be chosen from current trends and future directions in statistics. Therefore, the course content varies based upon the topic that both the student and the mentoring faculty member choose. The practicum experience provides students the opportunity to apply and integrate knowledge acquired through coursework.
Prerequisite: Consent of instructor.

STAT 6398. Research And Thesis. 3 Hours.

This course includes a study of research methods in statistics, identification of an appropriate thesis problem and the preparatory work leading to a plan for its solution. Study must be supervised by a member of the graduate statistics faculty.
Prerequisite: STAT 5362.

STAT 7330. Statistical Design & Methods I. 3 Hours.

STAT 7331. Statistical Desgn & Methods II. 3 Hours.

STAT 7365. Stat Mthd For Decision Making. 3 Hours.

Topics covered are oriented toward statistical methods supporting the decision environment. Topics include estimation, hypothesis testing, statistical modeling and decision methods.
Prerequisite: 3 Credit hour of graduate-level, introductory probability and statistics or the equivalent.

 

Director/Chair: Dustin L Jones

John G Alford, PHD, Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of Houston-Main; MS, Univ of Houston-Main; BS, Univ of Calif-Los Angeles

Emma Kathleen Price Bullock, PHD, Assistant Professor of Mathematics, Department of Mathematics & Statistics, PHD, Utah State University; MMATH, Utah State University; BS, Brigham Young University

Ferry B Butar, PHD, Professor of Statistics, Department of Mathematics & Statistics, PHD, Univ of Nebraska-Lincoln; MA, Univ of Nebraska-Lincoln; MS, Univ of Nebraska-Lincoln; BS, Academy of Statistics; DRS, University of Indonesia

Scott Thomas Chapman, PHD, Distinguished Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of North Texas; MS, Univ of N Carolina-Chapel Hill; BS, Wake Forest University; BS, Wake Forest University

Beth L Cory, PHD, Associate Professor of Mathematics Education, Department of Mathematics & Statistics, PHD, University of Virginia - SFS; MS, Florida State University; BS, Liberty University

Brandy Guntel Doleshal, PHD, Associate Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of Texas At Austin; BA, Indiana University; BS, Indiana University

Di Gao, PHD, Assistant Professor of Statistics, Department of Mathematics & Statistics, PHD, North Dakota State University; MA, Univ of Missouri-Columbia; BEC, Tianjin University; BBA, Tianjin University

Rebecca E Garcia, PHD, Professor of Mathematics, Department of Mathematics & Statistics, PHD, New Mexico State University; MA, Univ of Calif-Berkeley; BS, Loyola Marymount University

Damon Martin Hay, PHD, Associate Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of Houston-Main; MS, Univ of Houston-Main; BS, Univ of Texas At Austin

Melinda Ann Holt, PHD, Professor of Statistics and Associate Dean, COSET, Department of Mathematics & Statistics, PHD, Baylor University; MA, Baylor University; BA, Baylor University

William A. Jasper, PHD, Professor of Mathematics Education, Department of Mathematics & Statistics, PHD, Texas A&M University; MS, Univ of Southern California; BS, Lafayette College

Dustin L Jones, PHD, Professor of Mathematics Education and Chair, Mathematics and Statistics, Department of Mathematics & Statistics, PHD, Univ of Missouri-Columbia; MS, Texas A&M University; BS, Southwest Baptist University

Ram Chandra Kafle, PHD, Associate Professor of Statistics, Department of Mathematics & Statistics, PHD, Univ of South Florida; MS, Univ of Akron; MS, Tribhuvan University; BS, Tribhuvan University

Doo Young Kim, PHD, Assistant Professor of Statistics, Department of Mathematics & Statistics, PHD, Univ of South Florida; MA, Ball State University; BS, Gachon University

Naomi Lynne Krawzik, PHD, Assistant Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of North Texas; MS, Sam Houston State University; BS, Alma College

Brian M Loft, PHD, Associate Professor of Mathematics, Assistant Provost of Sponsored Programs, Department of Mathematics & Statistics, PHD, Univ of Oregon; MS, Texas State Univ-San Marcos; BS, Louisiana Tech University

Martin E Malandro, PHD, Associate Professor of Mathematics, Department of Mathematics & Statistics, PHD, Dartmouth College; AM, Dartmouth College; BS, Texas Tech University

Ananda Bandulasiri Manage, PHD, Professor of Statistics, Department of Mathematics & Statistics, PHD, Texas Tech University; MS, Texas Tech University; MS, Sam Houston State University; BS, University of Kelaniya

Taylor Elizabeth Martin, PHD, Associate Professor of Mathematics, Department of Mathematics & Statistics, PHD, Rice University; MA, Rice University; BA, Univ of Rochester; BS, Univ of Rochester

Amy E Ray, PHD, Assistant Professor of Mathematics, Department of Mathematics & Statistics, PHD, Michigan State University; MS, Michigan State University; MED, Texas Christian University; BS, Texas Christian University

Stephen Mark Scariano, PHD, Professor of Statistics, Department of Mathematics & Statistics, PHD, Texas Tech University; MS, Texas Tech University; BS, Loyola Univ-New Orleans

Mary B Swarthout, PHD, Associate Professor of Mathematics Education, Department of Mathematics & Statistics, PHD, Ohio State Univ; MA, Miami University; BA, Berea College

Edward W. Swim, PHD, Associate Professor of Mathematics, Department of Mathematics & Statistics, PHD, Texas Tech University; MS, Colorado School of Mines; BS, Angelo State University

Timothy O Trujillo, PHD, Assistant Professor of Mathematics, Department of Mathematics & Statistics, PHD, Univ of Denver; MS, New Mexico Inst/Mining/Tech; BS, New Mexico Inst/Mining/Tech

Linda Reichwein Zientek, PHD, Professor of Mathematics, Department of Mathematics & Statistics, PHD, Texas A&M University; MS, Sam Houston State University; BS, Sam Houston State University