Credit Limitations: Credit is not given for both Stat 251 and 301 or for both Stat 251 and 271.

Stat 150 Introduction to Statistics (3 cr). May be used as core credit in J-3-c. Intro to statistical reasoning with emphasis on examples and case studies; topics include design of experiments, descriptive statistics, measurement error, correlation and regression, probability, expectation, normal approximation, sample surveys, tests of significance.

Stat 251 Statistical Methods (3 cr). May be used as core credit in J-3-c. Cr is not given for Stat 251 after Stat 271 or Stat 301. 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. Prereq: Math 137, 143, 160, 170, or 2 yrs of high school algebra and permission.

Stat 262 Decision Analysis (1 cr). May be used as core credit in J-3-d. May not be taken for credit after Stat 271. An overview of basic components of decision theory, conditional probability, and Bayesian analysis. Prereq or coreq: Stat 251.

Stat 271 Statistical Inference and Decision Analysis (4 cr). May be used as core credit in J-3-d. Credit not allowed for both Stat 271 and 251 or for both Stat 271 and 301. Introduction to statistical methods including probability, decision theory, confidence intervals, hypothesis testing, correlation, regression, and nonparametric techniques. May involve evening exams. Prereq: Math 160 or 170.

Stat ID&WS301 Probability and Statistics (3 cr). WSU Math and Stat 360. Intended for engineers, mathematicians, and physical scientists. Cr not given for both Stat 251 and 301 or for both Stat 271 and 301. Intro to sample spaces, random variables, statistical distributions, hypothesis testing, basic experimental design, regression, and correlation. Prereq: Math 175.

Stat ID401 Statistical Analysis (3 cr). WSU Stat 401. 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. Prereq: Stat 251, 271, or 301.

Stat WS412 Biometry (3 cr). WSU Stat 412.

Stat WS-J420/WS-J520 Statistical Analysis of Qualitative Data (3 cr). WSU Stat 420/520.

Stat ID&WS422 Sample Survey Methods (3 cr). WSU Stat 422. Simple random, systematic, stratified random, one and two stage cluster sampling; introduction to variable probability sampling and estimation of population size. Two lec and one 1-hr lab a wk. Prereq: Stat 251, 271, or 301.

Stat 423 Beginning SAS Programming (1 cr). 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. Prereq: Stat 251, 271, or 301.

Stat 424 Intermediate SAS Programming (1 cr). SAS programming with several SAS modules such as SAS/Graph, SAS/IML, and SAS/Macro language. Prereq: Stat 251, 271, or 301 and Stat 423 or equivalent experience.

Stat 425 Topics in SAS Programming (1 cr). Topics in SAS programming, such as covering particular SAS modules in depth. Prereq: Stat 251, 271, or 301.

Stat ID428 Geostatistics (3 cr). See GeoE 428.

Stat 433 Econometrics (3 cr). See Econ 453.

Stat 446 Six Sigma Innovation (3 cr). Six Sigma is a highly structured strategy for acquiring, assessing, and applying customer, competitor, and enterprise intelligence for the purposes of product, system or enterprise innovation and design. It has two major thrusts, one that is directed toward significant innovation or improvement of an existing product, process or service that uses an approach called DMAIC (Define - Measure - Analyze - Improve - Control) and a second dedicated to design of new processes, products or services. This course focuses on the innovation aspects of Six Sigma. Recommended preparation: Stat 401. Prereq: Stat 251, Stat 271, or Stat 301. (Spring, alt/yrs)

Stat ID&WS451 Probability Theory (3 cr). See Math 451.

Stat ID&WS452 Mathematical Statistics (3 cr). See Math 452.

Stat ID&WS-J453/ID&WS-J544 Stochastic Models (3 cr). See Math J453/J538.

Stat 456 Quality Management (3 cr). See Bus 456.

Stat 498 (s) Internship (cr arr). Prereq: permission.

Stat 499 (s) Directed Study (cr arr). Prereq: permission.

Stat 500 Master's Research and Thesis (cr arr).

Stat 502 (s) Directed Study (cr arr). Prereq: permission.

Stat 503 (s) Workshop (cr arr). Prereq: permission.  

Stat 504 (s) Special Topics (cr arr). Prereq: permission.

Stat ID507 Experimental Design (3 cr). WSU 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. Prereq: Stat 401.

Stat WS513 Advanced Topics in Mathematical and Quantitative Methods (1-6 cr, max 12) WSU Stat 513. Topics may include advanced econometrics, dynamic optimizations, computer applications, methodology. Prereq: Permission.

Stat ID514 Nonparametric Statistics (3 cr). WSU 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; power, sample size, efficiency, and ARE. Prereq: Stat 401.

Stat WS518 Techniques of Sampling (3 cr) WSU Stat 518. Sample surveys for business use; theory and application with emphasis on appropriate sample types and the estimation of their parameters. Prereq: Permission.

Stat ID&WS519 Multivariate Analysis (3 cr). WSU Stat 519. The multivariate normal, Hotelling's T2, multivariate general linear model, discriminant analysis, covariance matrix tests, canonical correlation, and principle component analysis. Prereq: Stat 401.

Stat WS520 Statistical Analysis of Qualitative Data (3 cr). See Stat J420/J520.

Stat WS527 Quality Control (3 cr). WSU Stat 572. Simple quality assurance tools; process monitoring; Shewhart control charts; process characterization and capability; sampling inspection; factorial experiments.

Stat WS539 Time Series (3 cr). WSU Stat 516.

Stat WS542 Applied Stochastic Models (3 cr) WSU Stat 542. Stochastic processes, Markov models, stochastic dynamic programming, queues and simulation applied to business problems. Prereq: Permission.

Stat ID&WS544 Stochastic Models (3 cr). See Math J453/J538.

Stat WS548 Statistical Theory I (3 cr). WSU Math 568.

Stat WS549 Statistical Theory II (3 cr). WSU Math 569.

Stat ID&WS550 Regression (3 cr). WSU Stat 535. 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. Prereq: Math 330 and Stat 451. Coreq: Stat 452.

Stat WS552 Econometrics II (3 cr) WSU Stat 552. Econometric methods for systems estimation; simultaneous equations, discrete and limited dependent variable, panel data, and time series data. Prereq: Permission.

Stat ID555 Statistical Ecology (3 cr). See WLF 555.

Stat ID&WS565 Computer Intensive Statistics (3 cr). WSU Stat 536. 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. Prereq: Stat 451, Stat 452, Math 330, and computer programming experience or permission. (Alt/yrs)

Stat ID&WS571 Reliability Theory (3 cr). WSU Math 573. Statistical concepts; stochastic material strengths and lifetimes; strength versus safety analysis; reliability of coherent systems; maintenance models; complex systems. Prereq: Math 451. (Alt/yrs)

Stat ID&WS575 Theory of Linear Models (3 cr). WSU Stat 533. Theory of least squares analysis of variance models and the general linear hypothesis; small sample distribution theory for regression, fixed effects models, variance components models, and mixed models. Prereq: Stat 452 and Math 330.

Stat 594 Analysis of Correlated Data (3 cr) See For 594.

Stat 597 (s) Practicum (cr arr). Prereq: permission.

Stat 598 (s) Internship (cr arr). Prereq: permission.

Stat 599 (s) Non-thesis Master’s Research (cr arr). Research not directly related to a thesis or dissertation. Prereq: permission.