Rick L. Edgeman, Chair, Bi-State Department of Statistical Science (415 Carol Ryrie Brink Hall 83844-1104; phone 208/885-4410).
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. (Fall only)
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 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.
Stat 262 Decision Analysis (1 cr)
An overview of basic components of decision theory, conditional probability, and Bayesian analysis.
Prereq or Coreq: Stat 251
Stat 301 Probability and Statistics (3 cr)
Intended for engineers, mathematicians, and physical scientists. Cr not given for both Stat 251 and Stat 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.
Stat WS412 Biometry (3 cr) WSU Stat 412
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.
Stat 426 SAS Programming (3 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. 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 ID428 Geostatistics (3 cr)
See GeoE 428.
Stat 433 Econometrics (3 cr)
See Econ 453.
Stat ID446 Six Sigma Innovation (3 cr) WSU Stat 446
Same as Bus 446. 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. (Spring, Alt/yrs)
Stat 451 Probability Theory (3 cr)
See Math 451.
Stat 452 Mathematical Statistics (3 cr)
See Math 452.
Stat J453/J544 Stochastic Models (3 cr)
See Math J453/J538.
Stat 456 Quality Management (3 cr)
See Bus 456.
Stat 498 (s) Internship (cr arr)
Stat 499 (s) Directed Study (cr arr)
Stat 500 Master's Research and Thesis (cr arr)
Stat 501 (s) Seminar (cr arr)
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 (cr arr)
Stat 503 (s) Workshop (cr arr)
Stat 504 (s) Special Topics (cr arr)
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 511 Design for Six Sigma and Lean Management (3 cr)
See Bus 531.
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.
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. 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.
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.
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) WSU Stat 520
Stat WS522 Biostatistics and Statistical Epidemology (3 cr) WSU Stat 522
Rigorous approach to biostatistical and epidemiological methods including relative risk, odds ratio, cross-over designs, survival analysis and generalized linear models.
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 WS534 Analyses of Mixed Linear Models (3 cr) WSU Stat 534
Theory and applications of generalized linear mixed models, nonlinear mixed effects models and meta-analysis.
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.
Stat 544 Stochastic Models (3 cr)
See Math J453/J538.
Stat 546 Spatial Statistics (3 cr)
See Geog 542.
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.
Coreq: Stat 452
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. (Alt/yrs)
Stat WS566 Analyzing Microarray and Other Genomic Data (3 cr) WSU Stat 565
Statistical issues from pre-processing (transforming, normalizing) and analyzing genomic data (differential expression, pattern discovery and predictions).
Stat WS573 Probability (3 cr) WSU Stat 573
Probabilistic modeling and inference; product-limit estimator; probability plotting; maximum likelihood estimation with censored data; regression models for accelerated life testing.
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.
Stat 597 (s) Consulting Practicum (cr arr)
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 (cr arr)
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) Non-thesis Master's Research (cr arr)
Research not directly related to a thesis or dissertation.