Statistics Courses

Rick L. Edgeman, Chair, BiState Department of Statistical Science (415 Carol Ryrie Brink Hall 838441104; phone 208/8854410).
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 J3c. 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 J3c. 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 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)
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.
Stat 301 Probability and Statistics (3 cr)
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 chisquare, 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 1hr lab a wk.
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. Graded Pass/Fail.
Stat 424 Intermediate SAS Programming (1 cr)
SAS programming with several SAS modules such as SAS/Graph, SAS/IML, and SAS/Macro language. Graded Pass/Fail.
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. Graded Pass/Fail.
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)
Prereq: Stat 251, Stat 271, or Stat 301
Stat ID&WS451 Probability Theory (3 cr)
See Math 451.
Stat ID&WS452 Mathematical Statistics (3 cr) WSU Math and Stat 456
See Math 452.
Stat ID&WSJ453/ID&WSJ544 Stochastic Models (3 cr) WSU Stat 544
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 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 (16 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 ksample tests for location and scale, randomized complete blocks, rank correlation, and runs test. Permutation methods, nonparametric bootstrap methods, density estimation, curve smoothing, robust and rankbased 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.
Prereq: Permission
Stat ID&WS519 Multivariate Analysis (3 cr) WSU Stat 519
The multivariate normal, Hotelling's T^{2}, 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, crossover 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 metaanalysis.
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 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 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 pseudorandom 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)
Prereq: Stat 451, Stat 452, Math 330, and computer programming experience or Permission
Stat WS566 Analyzing Microarray and Other Genomic Data (3 cr) WSU Stat 565
Statistical issues from preprocessing (transforming, normalizing) and analyzing genomic data (differential expression, pattern discovery and predictions).
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. (Alt/yrs)
Prereq: Math 451
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 nonstatisticians, 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 preapproved.
Stat 599 (s) Nonthesis Master's Research (cr arr)
Research not directly related to a thesis or dissertation.
Prereq: Permission