Mathematics and Statistical Science
Hirotachi Abo, Chair (300 Carol Ryrie Brink Hall 83844-1103; phone 208-885-6742; mathstat@uidaho.edu); https://www.uidaho.edu/sci/mathstat.
The need for persons with quantitative skills is increasing dramatically as the world grows more complex. Mathematicians and statisticians have employment opportunities in business, industry, government, and teaching. Training in these fields, with their emphasis on problem solving, analysis, and critical thinking, is excellent preparation for graduate programs in engineering, science, business, or law. In fact, persons planning careers in almost any field will find their opportunities enhanced by the study of mathematics and statistics. The programs are intended to provide students just such enhancement. It is generally the case that the person who develops their quantitative skills has increased ability to attack many of the complex problems of society. Advances in science, technology, the social sciences, business, industry, and government become more and more dependent on precise analysis and the extraction of information from large quantities of data. Environmental problems, for example, require careful analysis by persons (or teams of persons) with skills in mathematics, statistics, and computer science as well as in biology, geology, physics, and many other fields.
Undergraduate Programs
The B.S. degree in Mathematics has four options: the general option, the applied computation option, the applied mathematical biology option, and the applied modeling and data science option.
The B.S. degree in statistics has two options: the general option and the actuarial science and finance option.
Minors are available in both Mathematics and Statistics.
Graduate Programs
Graduate degrees in mathematics include the M.S., M.A.T., and Ph.D. degrees. Graduate training in mathematics prepares students for careers in teaching or research and development. Employment opportunities include universities, colleges, industries, and government agencies. The Ph.D. is generally required for teaching and research at the university level. The M.S. qualifies students to teach at junior colleges, some four-year colleges, and for many positions in industry. The M.A.T. prepares students for secondary teaching and for some junior college positions. A baccalaureate degree in mathematics is generally required for admission to the graduate program; however, many students of science and technology can be admitted to the program with few undergraduate deficiencies.
In statistics, there is the master of science degree. Graduate study in statistics is designed for two types of students. Students whose undergraduate degrees are in subject matter disciplines will prepare for a career involving the application of statistical methods to their particular area of interest. Students with degrees in mathematics, computer science, or similar areas will prepare for a career in data analysis, statistical computing, teaching of introductory-level statistics, or to pursue a Ph.D. degree. Graduate certificate programs are also available in both statistical science and data science.
The M.A.T. in mathematics, M.S. in statistical science, and the certificate in statistical science are offered both on campus and online.
Faculty members in the Department of Mathematics and Statistical Science will be happy to answer questions about specific programs and courses. Such questions can also be addressed to the department chair.
MATH 108 Intermediate Algebra (3 credits)
Carries no credit after MATH 143. Review of algebra including factoring, rational expressions, exponents, radicals, quadratic equations, equations of lines. Taught using the Polya Math Center, a studio environment featuring group study, one-to-one interaction with instructors, computer-mediated modules, and lectures. Does not satisfy general education requirement.
MATH 123 Math in Modern Society (3 credits)
General Education: Mathematical Ways of Knowing
Discussion of some aspects of mathematical thought through the study of problems taken from areas such as logic, political science, management science, geometry, probability, and combinatorics; discussion of historical development and topics discovered in the past 100 years. Typically Offered: Fall, Spring and Summer.
MATH 143 Precalculus I: Algebra (3 credits)
General Education: Mathematical Ways of Knowing
Carries no credit after MATH 160 or MATH 170. Algebraic, exponential, logarithmic functions; graphs of conics; zeros of polynomials; systems of equations, induction. Taught using the Polya Math Center, a studio environment featuring group study, one-to-one interaction with instructors, computer-mediated modules, and lectures. Typically Offered: Fall, Spring and Summer.
Prereqs: Sufficient score on SAT, ACT, or math placement test; or MATH 108 with grade of C or better. It is recommended that MATH 143 be taken within two years of passing MATH 108 or its equivalent. Required test scores can be found here: http://www. uidaho. edu/registrar/registration/placement
MATH 144 Precalculus II: Trigonometry (1 credit)
Trigonometric functions, inverse functions, applications. Taught using the Polya Math Center, a studio environment featuring group study, one-to-one interaction with instructors, computer-mediated modules, and lectures. Typically Offered: Fall, Spring and Summer. Prereqs or
MATH 153 Introduction to Statistical Reasoning (3 credits)
General Education: Mathematical Ways of Knowing
Cross-listed with STAT 153
A course in statistical literacy, an introduction with emphasis on examples and case studies. Topics include data sources and the distinction between experiments, observational studies, and surveys; graphical and numerical description of data; understanding randomness; central tendency; correlation versus causation; line of best fit; estimation of proportions; and statistical testing.
MATH 160 Survey of Calculus (4 credits)
General Education: Mathematical Ways of Knowing
Carries no credit after MATH 170. Overview of functions, and graphs, derivatives, integrals, exponential and logarithmic functions, functions of several variables, and differential equations. Primarily for students who need only one semester of calculus, such as students in business or architecture. Typically Offered: Fall, Spring and Summer.
Prereqs: Sufficient score on SAT, ACT, or math placement test, or MATH 143 with a C or better. Required test scores can be found here: http://www. uidaho. edu/registrar/registration/placement.
MATH 170 Calculus I (4 credits)
General Education: Mathematical Ways of Knowing
Carries 2 credits after MATH 160. Functions, limits, continuity, differentiation, integration, applications, differentiation and integration of transcendental functions. Primarily for students in engineering, mathematics, science or computer science. Typically Offered: Fall, Spring and Summer.
Prereqs: MATH 143 (with a grade of C or better) and MATH 144 (concurrent enrollment in MATH 144 is allowed although it is recommended that students complete MATH 144 before enrolling in MATH 170); or demonstrated proficiency through a sufficiently high score on the ACT, SAT, or math placement test. Required test scores can be found here: http://www. uidaho. edu/registrar/registration/placement.
MATH 175 Calculus II (4 credits)
General Education: Mathematical Ways of Knowing
Differentiation and integration of transcendental functions, integration techniques, general mean value theorem, numerical techniques, and series. Typically Offered: Fall, Spring and Summer.
Prereqs: MATH 170 with a grade of C or better
MATH 176 Discrete Mathematics (3 credits)
Induction, set theory, graph theory, number systems, Boolean algebra, and elementary counting.
Prereqs: MATH 143 or sufficiently high score on SAT, ACT, or math placement test. Required test scores can be found here: http://www. uidaho. edu/registrar/registration/placement.
MATH 183 Introduction to Data Science in Python (3 credits)
The purpose of this course is to introduce fundamental skills in data science such as data manipulation, data visualization, and tabular data analysis, as well as the basic usage of Python and Python techniques to perform such skills. Relevant mathematical topics such as basic linear algebra and basic statistics will also be introduced as required.
MATH 204 (s) Special Topics (1-16 credits)
Credit arranged
MATH 215 Proof via Number Theory (3 credits)
An introduction to mathematical thinking and proof through the development of the basic results of elementary number theory. Emphasis on techniques of mathematical proofs, reading and writing proofs, and fundamental mathematical structures.
MATH 275 Calculus III (3 credits)
General Education: Mathematical Ways of Knowing
Vectors, functions of several variables, and multiple integration. Typically Offered: Fall, Spring and Summer.
Prereqs: MATH 175
MATH 299 (s) Directed Study (1-16 credits)
Credit arranged
MATH 310 Ordinary Differential Equations (3 credits)
Classification, initial and boundary value problems of one variable, exact equations, methods of solving higher-order linear equations, second-order equations with constant coefficient, series solutions, systems of linear equations, Laplace transforms, and existence theorems. Recommended preparation: MATH 275.
Prereqs: MATH 175
MATH 315 HON:Topics in Pure Mathematics (3 credits)
A topic selected each year that develops skill and appreciation for theoretical nature of mathematics.
Prereqs: Permission of director of University Honors Program
MATH 330 Linear Algebra (3 credits)
Linear equations, matrices, linear transformations, eigenvalues, diagonalization; applications. Recommended Preparation: MATH 175.
MATH 371 Mathematical Physics (3 credits)
Cross-listed with PHYS 371
Mathematical techniques needed in upper-division physics courses, including vector analysis, matrices, Sturm-Liouville problems, special functions, partial differential equations, complex variables. Typically Offered: Fall (Even Years).
MATH 376 Discrete Mathematics II (3 credits)
Selected topics from discrete mathematics such as graph theory, modeling, and optimization. Recommended for Computer Science majors.
Prereqs: MATH 176 or Permission
MATH 385 Theory of Computation (3 credits)
Cross-listed with CS 385
Mathematical models of computation, including finite automata and Turing machines. Typically Offered: Fall.
MATH 386 Theory of Numbers (3 credits)
Second course on number theory, including a historical treatment of efforts to answer basic questions on the density and possible forms of prime numbers. Topics may include: quadratic reciprocity, cubic reciprocity, quadratic forms, genus theory, higher reciprocity laws, Hilbert class field, the prime number theorem, Dirichlet's theorem on primes in an arithmetic progression, elliptic curves, and modular forms.
Prereqs: MATH 215
MATH 388 History of Mathematics (3 credits)
History of the development of mathematical ideas from ancient cultures to the present, including the relationship of those ideas to the cultures that produced them as well as an understanding of the mathematics involved. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 175 or Permission
MATH 390 Axiomatic Geometry (3 credits)
Development of Euclidean and hyperbolic geometry using the axiomatic approach. Recommended Preparation: MATH 215.
Prereqs: High school geometry and MATH 176, or Instructor Permission
MATH 391 Modern Geometry (3 credits)
Euclidean and non-Euclidean geometries, plus topics chosen from projective, transformational, and computational geometry. Recommended Preparation: MATH 215.
Prereqs: High School Geometry and MATH 176, or Instructor Permission
MATH 395 Analysis of Algorithms (3 credits)
Cross-listed with CS 395
Measures of efficiency; standard methods and examples in the design, implementation, and analysis of algorithms. (Spring only)
MATH 400 (s) Seminar (1-16 credits)
Credit arranged
MATH 404 (s) Special Topics (1-16 credits)
Credit arranged
MATH 415 Cryptography (3 credits)
General Education: Senior Experience
Congruences, modular arithmetic, private-key cryptosystems, public-key cryptosystems, and applications. The role of modern mathematics in information age society.
Prereqs: MATH 330
MATH 420 Complex Variables (3 credits)
Complex numbers, elementary functions, derivatives, the residue theorem, conformal mappings, contour integration, infinite series, applications.
Prereqs: MATH 275
MATH 426 Discrete Optimization (3 credits)
Optimization on graphs, networks and flows, and related topics. Recommended Preparation: MATH 175.
MATH 427 Transformational Geometry (3 credits)
Geometry concepts of congruence, parallelism, and similarity using rigid motions; the group structure of the collection of isometries and their matrix representations. The course is of particular interest to secondary mathematics teaching majors.
Prereqs: MATH 330 or equivalent
MATH 428 Numerical Methods (3 credits)
Cross-listed with ENGR 428, PHYS 428
Joint-listed with MATH 529, PHYS 528
Systems of equations, eigenvalues and eigenvectors, root finding, error analysis, numerical solution to differential equations, interpolation and data fitting, numerical integration, related topics and applications, such as fast Fourier transforms, as time and interest permits. Typically Offered: Spring.
Prereqs: Math 310; and CS 120 or Math 183 or ENGR 212 or Permission
MATH 430 Advanced Linear Algebra (3 credits)
Vector spaces, linear transformations, characteristic polynomial, eigenvectors, Hermitian and unitary operators, inner products, quadratic forms, Jordan canonical form, applications.
MATH 432 Numerical Linear Algebra (3 credits)
Analysis of efficiency and accuracy of large linear algebra problems; special emphasis on solving linear equations and finding eigenvalues.
Prereqs: MATH 275, MATH 330, and knowledge of a computer language
MATH 437 Mathematical Biology (3 credits)
General Education: Senior Experience
Modeling biological phenomena, mostly through differential equations; mathematical topics include stability analysis and limit cycles for nonlinear ODE's, spatial diffusion and traveling waves for PDE's; biological topics include models of predator-prey systems, infectious diseases, and competition.
Prereqs: MATH 310 or Permission Cooperative: open to WSU degree-seeking students.
MATH 438 Mathematical Modeling (3 credits)
Topics in the use of mathematics to model phenomena from science, business, economics, and engineering.
Prereqs: CS 120, MATH 310 and MATH 330, or Instructor Permission
MATH 451 Probability Theory (3 credits)
Cross-listed with STAT 451
Random variables, expectation, special distributions (normal, binomial, exponential, etc. ), moment generating functions, law of large numbers, central limit theorem. Cooperative: open to WSU degree-seeking students. (Fall only)
Prereqs or Coreqs: MATH 275 or Permission
MATH 452 Mathematical Statistics (3 credits)
Cross-listed with STAT 452
Estimation of parameters, confidence intervals, hypothesis testing, likelihood ratio test, sufficient statistics. Cooperative: open to WSU degree-seeking students. (Spring only)
Prereqs: MATH 451 or Permission
MATH 453 Stochastic Models (3 credits)
Cross-listed with STAT 453
Joint-listed with MATH 538
Markov chains, stochastic processes, and other stochastic models; applications. Additional projects/assignments required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 451 or Permission.
MATH 455 Applied Actuarial Science (1 credit)
Risk problems on the actuarial exam. Graded P/F.
Prereqs: MATH 451
MATH 461 Abstract Algebra I (3 credits)
Groups, rings, and fields. (Fall only)
MATH 471 Introduction to Analysis I (3 credits)
Topology of Euclidean n-space, limit and continuity, differentiation, integration. (Fall only)
MATH 472 Introduction to Analysis II (3 credits)
Topology of Euclidean n-space, limit and continuity, differentiation, integration. (Spring only)
Prereqs: MATH 471 or Permission
MATH 476 Combinatorics (3 credits)
Elementary counting methods, generating functions, recurrence relations, Polya's enumeration, enumeration of graphs, trees, searching, combinatorial algorithms. Recommended Preparation: MATH 176, or MATH 215, or MATH 376.
MATH 480 Partial Differential Equations (3 credits)
Intro to Fourier analysis, application to solution of partial differential equations; classical partial differential equations of engineering and physics.
Prereqs: MATH 310 or Permission
MATH 483 Foundations of Machine Learning (3 credits)
This course covers mathematical foundations as well as basic algorithms for machine learning. Topics include algorithms for classification, regression, and clustering such as support vector machines, decision tree learning, and K-means; dimensionality reduction for data compression; and deep learning. The implementation of the algorithms will be in Python. Typically Offered: Varies.
MATH 499 (s) Directed Study (1-16 credits)
Credit arranged
MATH 500 Master's Research and Thesis (1-16 credits)
Credit arranged
MATH 501 (s) Seminar (1-16 credits)
Credit arranged
MATH 502 (s) Directed Study (1-16 credits)
Credit arranged
MATH 504 (s) Special Topics (1-16 credits)
Credit arranged
MATH 505 (s) Professional Development (1-16 credits)
Credit arranged. Credit earned in this course will not be accepted toward graduate degree programs.
MATH 510 Seminar on College Teaching of Mathematics (1 credit, max arranged)
Development of skills in the teaching of college mathematics; includes structure of class time, test construction, and various methods of teaching mathematics; supervision of teaching assistants in their beginning teaching assignments. Graded P/F.
Prereqs: Permission
MATH 521 Topology I (3 credits)
Basic concepts of point set and algebraic topology. Cooperative: open to WSU degree-seeking students.
MATH 523 Algebraic Topology I (3 credits)
Basic homotopy theory, covering spaces, homology theory, and applications.
MATH 528 Differentiable Manifolds (3 credits)
Fundamentals of smooth manifolds, tangent spaces, vector fields, Lie groups, integration on manifolds, and applications. Cooperative: open to WSU degree-seeking students.
MATH 529 Numerical Methods (3 credits)
Cross-listed with PHYS 528
Joint-listed with ENGR 428, MATH 428, and PHYS 428
Systems of equations, root finding, error analysis, numerical solution to differential equations, interpolation and data fitting, numerical integration, related topics and applications. Additional projects and/or assignments required for graduate credit in PHYS 528.
Prereqs: MATH 310.
MATH 531 Complex Variables (3 credits)
Theory of functions of a complex variable. Cooperative: open to WSU degree-seeking students.
MATH 535 Real Variables (3 credits)
Measure and integration theory for functions of one or several variables.
MATH 536 Probability Theory (3 credits)
Random variables, characteristic functions, convergence theorems, central limit theorem, conditional probability, and stochastic processes as developed from a measure theoretic basis.
Prereqs: MATH 535 or Permission
MATH 537 Fourier Analysis (3 credits)
Basic properties of Fourier series, convergence of Fourier series, Fourier transforms, finite Fourier analysis, and applications to signal processing such as frames and wavelets. Recommended preparation: MATH 471 and 472; or Permission. Typically Offered: Varies. Cooperative: open to WSU degree-seeking students.
MATH 538 Stochastic Models (3 credits)
Joint-listed with MATH 453 and STAT 453
Markov chains, stochastic processes, and other stochastic models; applications. Additional projects/assignments required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 451 or Permission.
MATH 539 Theory of Ordinary Differential Equations (3 credits)
Existence, uniqueness, and stability of solutions of first-order systems; other topics. Cooperative: open to WSU degree-seeking students.
MATH 540 Partial Differential Equations (3 credits, max 3)
Existence and uniqueness theorems for the wave, heat, and Laplace's equations of physics; additional topics such as nonlinear models in mathematical biology, perturbation methods, etc. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 539 or Permission
MATH 555 Groups and Fields I (3 credits)
Groups, fields, polynomials, Galois theory, representation theory. Cooperative: open to WSU degree-seeking students.
MATH 556 Groups and Fields II (3 credits)
Groups, fields, polynomials, Galois theory, representation theory. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 555 or Permission
MATH 557 Ring Theory (3 credits)
Rings, ideals, modules, commutative algebra. Cooperative: open to WSU degree-seeking students.
MATH 558 Introduction to Algebraic Geometry (3 credits)
Affine and projective varieties, morphisms, functions on varieties, birational maps, applications. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 557 or Permission
MATH 559 Algebraic Number Theory (3 credits)
Dedekind rings, algebraic integers, prime ideals and their splittings, decomposition group, inertia group, ideal class group, quadratic extensions and cyclotomic extensions. Some class field theory, including Frobenius automorphism, Artin automorphism, Hilbert class field, adeles and ideles.
Prereqs: MATH 557 or permission.
MATH 561 (s) Seminar in Algebra (1-3 credits, max arranged)
Current literature.
MATH 563 Mathematical Genetics (3 credits)
Cross-listed with BIOL 563
Investigation of aspects of evolutionary biology with an emphasis on stochastic models and statistical methods; topics include: diffusion methods in molecular evolution, gene genealogies and the coalescent, inferring coalescent times from DNA sequences, population subdivision and F statistics, likelihood methods for phylogenic inference, statistical hypothesis testing, the parametric bootstrap. Cooperative: open to WSU degree-seeking students.
MATH 571 Functional Analysis I (3 credits)
Linear topological spaces and linear operators.
Prereqs: MATH 535
MATH 572 Functional Analysis II (3 credits)
Linear topological spaces and linear operators.
Prereqs: MATH 571
MATH 575 Graph Theory I (3 credits)
Basic concepts and theorems; topics include trees and connectivity, eulerian and hamiltonian graphs, graph colorings, matchings, graph decomposition, and extremal graph theory.
MATH 576 Graph Theory II (3 credits)
Basic concepts and theorems; topics include trees and connectivity, eulerian and hamiltonian graphs, graph colorings, matchings, graph decomposition, and extremal graph theory.
Prereqs: Instructor Permission
MATH 579 Combinatorics (3 credits)
Topics from enumerative combinatorics, design theory, extremal combinatorics and algebraic combinatorics.
MATH 596 MAT Comp Exam (1 credit)
Supervised preparation for the Master of Arts in Teaching comprehensive exam. Graded P/F.
MATH 598 (s) Internship (1-16 credits)
Credit arranged
MATH 599 (s) Non-thesis Master's Research (1-16 credits)
Credit arranged. Research not directly related to a thesis or dissertation.
Prereqs: Permission
MATH 600 Doctoral Research and Dissertation (1-45 credits)
Credit arranged
MTHE 235 Mathematics for Elementary Teachers I (3 credits)
Mathematical development of arithmetic and problem solving as those subjects are currently taught in elementary schools. Three lectures and one 1-hour lab per week. Typically Offered: Fall, Spring.
MTHE 236 Mathematics for Elementary Teachers II (3 credits)
Mathematical development of informal geometry, problem solving, and probability and statistics as those subjects are currently taught in elementary schools. Three lectures and one 1-hour lab per week.
Prereqs: MTHE 235
MTHE 409 Algebraic and Functional Reasoning (3 credits)
Examines the understandings that are foundational to advanced algebraic concepts, and how grade 5-10 students develop these ideas. Topics include strategies for solving equations and systems, covariational reasoning, properties of linear, quadratic, exponential, and trigonometric functions.
MTHE 410 Proof and Viable Argumentation (3 credits)
Develops viable argumentation as it can be found in grades 5-10 as a means of learning content, deepening understanding, and determining what is true and what is false mathematically. Topics include the language of argumentation, argument types, reasoning types, the distinction between proofs and viable arguments. Emphasizes how different argument types can contribute to student learning and increasing student discourse.
MTHE 513 Problem Solving Through History (3 credits)
Historical study of approaches to solving problems in geometry, number theory, and set theory. This course is specifically designed for the M. A. T. program in Mathematics and will not satisfy the requirements of other mathematics degree programs.
MTHE 516 Groups and Symmetry (3 credits)
Exploration of groups, symmetry, and permutations. This course is specifically designed for the M. A. T. program in Mathematics and will not satisfy the requirements of other mathematics degree programs.
STAT 153 Introduction to Statistical Reasoning (3 credits)
General Education: Mathematical Ways of Knowing
Cross-listed with MATH 153
A course in statistical literacy, an introduction with emphasis on examples and case studies. Topics include data sources and the distinction between experiments, observational studies, and surveys; graphical and numerical description of data; understanding randomness; central tendency; correlation versus causation; line of best fit; estimation of proportions; and statistical testing. Typically Offered: Fall, Spring and Summer.
STAT 204 (s) Special Topics (1-16 credits)
Credit arranged
STAT 251 Statistical Methods (3 credits)
General Education: Mathematical Ways of Knowing
Intro to statistical methods including design of statistical studies, basic sampling methods, descriptive statistics, probability and sampling distributions; inference in surveys and experiments, regression, and analysis of variance. (Credit will not be awarded for STAT 251 after STAT 301 or STAT 416, or for STAT 416 after STAT 251 or STAT 301. ) Typically Offered: Fall, Spring and Summer.
Prereqs: MATH 108 (with grade of C or better) or MATH 143 or MATH 160 or MATH 170 or sufficient score on SAT, ACT, or math placement test (see www. uidaho. edu/registrar/registration/placement).
STAT 299 (s) Directed Study (1-16 credits)
Credit arranged
STAT 301 Probability and Statistics (3 credits)
Credit not awarded for STAT 251 after STAT 301. Intended for engineers, mathematicians, and physical scientists. Intro to sample spaces, random variables, statistical distributions, hypothesis testing, basic experimental design, regression, and correlation.
Prereqs: MATH 175.
STAT 404 (s) Special Topics (1-16 credits)
Credit arranged
STAT 407 Experimental Design (3 credits)
Joint-listed with STAT 507
Methods of constructing and analyzing designs for experimental investigations; analysis of designs with unequal subclass numbers; concepts of blocking randomization and replication; confounding in factorial experiments; incomplete block designs; response surface methodology. Additional work required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: STAT 431
STAT 414 Nonparametric Statistics (3 credits)
Joint-listed with STAT 514
Conceptual development of nonparametric methods including one, two, and k-sample tests for location and scale, randomized complete blocks, rank correlation, and runs test. Permutation methods, nonparametric bootstrap methods, density estimation, curve smoothing, robust and rank-based methods for the general linear model, and comparison. Comparison to parametric methods. Additional coursework/project required for graduate credit. Typically Offered: Varies.
Prereqs: STAT 431 Cooperative: open to WSU degree-seeking students.
STAT 417 Statistical Learning and Predictive Modeling (3 credits)
Joint-listed with STAT 517
A comprehensive overview of statistical learning and predictive modeling techniques to analyze large data sets in science, social science, and other data-rich fields including, for example, biology, business, and engineering. Topics include regression, classification, resampling methods, model selection and regularization, tree-based methods, support vector machines, clustering, and text mining. The implementation of the methods will be in R and Python as needed. Basic experience with computer programming is assumed. Additional coursework/project required for graduate credit. Typically Offered: Fall.
Prereqs: STAT 431
STAT 418 Multivariate Analysis (3 credits)
Joint-listed with STAT 519
The multivariate normal, Hotelling's T2, multivariate general linear model, discriminant analysis, covariance matrix tests, canonical correlation, and principle component analysis. Additional coursework/project required for graduate credit. Typically Offered: Spring.
Prereqs: STAT 431 Cooperative: open to WSU degree-seeking students.
STAT 419 Introduction to SAS/R Programming (3 credits)
An introduction to the SAS and R programming languages. Topics include creating data, importing data, accessing subsets of data, exporting data, plotting and graphing, loops and functions. Course provides a basic knowledge of SAS and R to help students master statistical tools available in SAS and R, including basic statistical analyses.
STAT 422 Survey Sampling Methods (3 credits)
Introduction to survey sampling designs and inference including simple, stratified, and cluster sampling; ratio and regression estimators, unequal probability sampling, and population size estimation. Cooperative: open to WSU degree-seeking students.
STAT 426 SAS Programming (3 credits)
Coverage of a variety of methods for data manipulation, data management, and programming in the SAS language. DATA step programming methods including data transformation, functions for numeric and character data, input of complicated data files, and do loop usage. Data management topics include concatenating data files, sorting and merging data files and ARRAY statement usage. SAS programming with SAS modules such as SAS/Graph, SAS/IML, and SAS/Macro language. Other topics in SAS programming, such as covering other SAS modules in depth.
STAT 427 R Programming (3 credits)
Credit not awarded for STAT 427 after STAT 419. Introduction to the R computing language for scientific graphics, statistical analysis, simulation, and mathematical modeling. Topics include functions, data management and manipulation, loops and logical structures, vector and matrix calculations, contemporary graphical displays, probability and simulation, dynamic models, numerical optimization, standard methods of statistical analysis.
STAT 431 Statistical Analysis (3 credits)
Concepts and methods of statistical research including multiple regression, contingency tables and chi-square, experimental design, analysis of variance, multiple comparisons, and analysis of covariance. Cooperative: open to WSU degree-seeking students.
STAT 433 Econometrics (3 credits)
Cross-listed with ECON 453
Application of statistical methods to economics and business studies; emphasis on regression analysis methods.
STAT 435 Introduction to Bayesian Statistics (3 credits)
Joint-listed with STAT 535
Exploring the basics of Bayesian thinking with a comparative approach to interpretations of probability. Statistical methods, Bayesian approach to statistical inference. Methods include point and interval estimation under the Normal model, and inference under hierarchical models with emphasis on statistical model building. Computational methods, applications of methods useful for sampling posterior distributions such as rejection sampling, importance sampling, and Markov Chain Monte Carlo. Additional coursework/project required for graduate credit. Typically Offered: Varies.
Prereqs: STAT 431 or equivalent
STAT 436 Applied Regression Modeling (3 credits)
General Education: Senior Experience
Joint-listed with STAT 516
Statistical modeling and analysis of scientific data using regression model including linear, nonlinear, and generalized linear regression models. Topics also include analysis of survival data, censored and truncated response variables, categorical response variables, and mixed models. Emphasis is on application of these methods through the analysis of real data sets with statistical packages. Additional coursework/projects will be assigned at the 500-level. Typically Offered: Spring.
Prereqs: STAT 431
STAT 451 Probability Theory (3 credits)
Cross-listed with MATH 451
Random variables, expectation, special distributions (normal, binomial, exponential, etc. ), moment generating functions, law of large numbers, central limit theorem. Cooperative: open to WSU degree-seeking students. (Fall only)
Prereqs or Coreqs: MATH 275 or Permission
STAT 452 Mathematical Statistics (3 credits)
Cross-listed with MATH 452
Estimation of parameters, confidence intervals, hypothesis testing, likelihood ratio test, sufficient statistics. Cooperative: open to WSU degree-seeking students. (Spring only)
Prereqs: MATH 451 or Permission
STAT 453 Stochastic Models (3 credits)
Cross-listed with MATH 453
Joint-listed with MATH 538
Markov chains, stochastic processes, and other stochastic models; applications. Additional projects/assignments required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 451 or Permission
STAT 456 Enterprise Quality Management (3 credits)
Cross-listed with OM 456
Principles of quality management, with a focus on Lean Six Sigma concepts and Define-Measure-Analyze-Improve-Control (DMAIC) approach to managing and improving enterprise quality. Additional work required for graduate credit. May include evening exams. May involve field trips. Typically Offered: Varies.
STAT 498 (s) Internship (1-16 credits)
Credit arranged
Prereqs: Permission
STAT 499 (s) Directed Study (1-16 credits)
Credit arranged
STAT 500 Master's Research and Thesis (1-16 credits)
Credit arranged
STAT 501 (s) Seminar (1-16 credits)
Credit arranged. This course addresses statistical ethics; statistically oriented research; and deeper and more extensive consideration of topics relevant to but not addressed in other graduate level statistics courses offered during that semester. Formal presentations and reports in journal format are used to enhance written, oral, and presentation communication experience and ability.
STAT 502 (s) Directed Study (1-16 credits)
Credit arranged
STAT 503 (s) Workshop (1-16 credits)
Credit arranged
STAT 504 (s) Special Topics (1-16 credits)
Credit arranged
STAT 507 Experimental Design (3 credits)
Joint-listed with STAT 407
Methods of constructing and analyzing designs for experimental investigations; analysis of designs with unequal subclass numbers; concepts of blocking randomization and replication; confounding in factorial experiments; incomplete block designs; response surface methodology. Additional work required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: STAT 431
STAT 514 Nonparametric Statistics (3 credits)
Joint-listed with STAT 414
Conceptual development of nonparametric methods including one, two, and k-sample tests for location and scale, randomized complete blocks, rank correlation, and runs test. Permutation methods, nonparametric bootstrap methods, density estimation, curve smoothing, robust and rank-based methods for the general linear model, and comparison. Comparison to parametric methods. Additional coursework/project required for graduate credit. Typically Offered: Varies. Cooperative: open to WSU degree-seeking students.
Prereqs: STAT 431
STAT 516 Applied Regression Modeling (3 credits)
General Education: Senior Experience
Joint-listed with STAT 436
Statistical modeling and analysis of scientific data using regression model including linear, nonlinear, and generalized linear regression models. Topics also include analysis of survival data, censored and truncated response variables, categorical response variables, and mixed models. Emphasis is on application of these methods through the analysis of real data sets with statistical packages. Additional coursework/projects will be assigned at the 500-level. Typically Offered: Spring.
STAT 517 Statistical Learning and Predictive Modeling (3 credits)
Joint-listed with STAT 417
A comprehensive overview of statistical learning and predictive modeling techniques to analyze large data sets in science, social science, and other data-rich fields including, for example, biology, business, and engineering. Topics include regression, classification, resampling methods, model selection and regularization, tree-based methods, support vector machines, clustering, and text mining. The implementation of the methods will be in R and Python as needed. Basic experience with computer programming is assumed. Additional coursework/project required for graduate credit. Typically Offered: Fall.
STAT 519 Multivariate Analysis (3 credits)
Joint-listed with STAT 418
The multivariate normal, Hotelling's T2, multivariate general linear model, discriminant analysis, covariance matrix tests, canonical correlation, and principle component analysis. Additional coursework/project required for graduate credit. Typically Offered: Spring. Cooperative: open to WSU degree-seeking students.
Prereqs: STAT 431
STAT 535 Introduction to Bayesian Statistics (3 credits)
Joint-listed with STAT 435
Exploring the basics of Bayesian thinking with a comparative approach to interpretations of probability. Statistical methods, Bayesian approach to statistical inference. Methods include point and interval estimation under the Normal model, and inference under hierarchical models with emphasis on statistical model building. Computational methods, applications of methods useful for sampling posterior distributions such as rejection sampling, importance sampling, and Markov Chain Monte Carlo. Additional coursework/project required for graduate credit. Typically Offered: Varies.
Prereqs: STAT 431 or equivalent
STAT 544 Stochastic Models (3 credits, max 3)
Cross-listed with MATH 538
Joint-listed with STAT 453
Markov chains, stochastic processes, and other stochastic models; applications. Additional projects/assignments required for graduate credit. Cooperative: open to WSU degree-seeking students.
Prereqs: MATH 451 or Permission.
STAT 550 Regression (3 credits)
Theory and application of regression models including linear, nonlinear, and generalized linear models. Topics include model specification, point and interval estimators, exact and asymptotic sampling distributions, tests of general linear hypotheses, prediction, influence, multicollinearity, assessment of model fit, and model selection. Recommended preparation: MATH 330 and STAT 452.
STAT 555 Statistical Ecology (3 credits)
Cross-listed with WLF 555
Stochastic models in ecological work; discrete and continuous statistical distributions, birth-death processes, diffusion processes; applications in population dynamics, population genetics, ecological sampling, spatial analysis, and conservation biology. Cooperative: open to WSU degree-seeking students. (Spring, alt/years)
Prereqs: MATH 451 or Permission
STAT 565 Computer Intensive Statistics (3 credits)
Numerical stability, matrix decompositions for linear models, methods for generating pseudo-random variates, interactive estimation procedures (Fisher scoring and EM algorithm), bootstrapping, scatterplot smoothers, Monte Carlo techniques including Monte Carlo integration and Markov chain Monte Carlo. Cooperative: open to WSU degree-seeking students. (Alt/years)
Prereqs: STAT 451, STAT 452, MATH 330, and computer programming experience or Permission
STAT 597 (s) Consulting Practicum (1-16 credits)
Credit arranged. Students will gain experience in statistical consulting and data analysis, using multiple statistical software packages in the analysis process. Topics include communication of statistical information and analysis to non-statisticians, ethics, and computing. Emphasis is placed on written and oral presentation of statistical analysis plans and results.
STAT 598 (s) Internship (1-16 credits)
Credit arranged. Students gain experience in statistical consultation and/or statistical data analysis in their present place of employment or an arranged internship organization. Students are jointly accountable to a faculty advisor and a person providing oversight of the individual’s efforts within the organization. All internship experiences must be pre-approved.
STAT 599 (s) Research (1-16 credits)
Credit arranged. Research not directly related to a thesis or dissertation.