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# Statistics Courses

Christopher Williams, Chair, Bi-State Department of Statistical Science (415 Carol Ryrie Brink Hall 83844-1104; phone 208/885-4410).

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

Stat 150 Introduction to Statistics (3 cr)

May be used as general education 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 general education credit in J-3-c. Credit awarded for only one of Stat 251, Stat 301, and Stat 416. 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 108, Math 137, Math 143, Math 160, Math 170, or 2 yrs of high school algebra and Permission

Stat 301 Probability and Statistics (3 cr)

Credit awarded for only one of Stat 251, Stat 301, and Stat 416. Intended for engineers, mathematicians, and physical scientists. Intro to sample spaces, random variables, statistical distributions, hypothesis testing, basic experimental design, regression, and correlation.

Prereq: Math 175

Stat 416 Statistical Methods for Research (3 cr)

Credit awarded for only one of Stat 251, Stat 301, and Stat 416. Concepts and methods in quantitative research including observational and experimental study design, point estimation, hypothesis testing, effect size, sample size, causation, one and two-way ANOVA, simple linear regression, interpreting and reporting results.

Prereq: Math 137, Math 143, Math 160, Math 170, or two years of high school algebra and permission

Stat 422 Sample Survey Methods (3 cr)

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. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 251 or Stat 301

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.

Prereq: Stat 251 or Stat 301

Stat 428 Geostatistics (3 cr)

See GeoE 428. Cooperative: open to WSU degree-seeking students.

Stat 431 Statistical Analysis (3 cr)

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.

Prereq: Stat 251, Stat 301, or Stat 416

Stat 433 Econometrics (3 cr)

See Econ 453.

Stat 446 Six Sigma Innovation (3 cr)

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 431. Cooperative: open to WSU degree-seeking students. (Spring, Alt/yrs)

Prereq: Stat 251 or Stat 301

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)

Prereq: Permission

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 507 Experimental Design (3 cr)

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. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 431

Stat 511 Design for Six Sigma and Lean Management (3 cr)

See Bus 531.

Stat 514 Nonparametric Statistics (3 cr)

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. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 431

Stat 516 Applied Regression Modeling (3 cr)

Statistical modeling and analysis of scientific date 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.

Prereq: Stat 431

Stat 519 Multivariate Analysis (3 cr)

The multivariate normal, Hotelling's T2, multivariate general linear model, discriminant analysis, covariance matrix tests, canonical correlation, and principle component analysis. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 431

Stat 544 Stochastic Models (3 cr)

See Math J453/J538.

Stat 546 Spatial Statistics (3 cr)

See Geog 542.

Stat 550 Regression (3 cr)

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. Cooperative: open to WSU degree-seeking students.

Prereq: Math 330 and Stat 451

Coreq: Stat 452

Stat 555 Statistical Ecology (3 cr)

See WLF 555. Cooperative: open to WSU degree-seeking students.

Stat 565 Computer Intensive Statistics (3 cr)

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/yrs)

Prereq: Stat 451, Stat 452, Math 330, and computer programming experience or Permission

Stat 575 Theory of Linear Models (3 cr)

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. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 452 and Math 330

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.

Prereq: Permission