WSU Graduate Courses - Statistics/STT

STT 520 BIOSTATISTICS FOR HEALTH PROFESSIONALS (Credits: 4)

Introduction to the basic principles and applications of statistical methods as they are applied to data arising in the health professions.

STT 560 APPLIED STATISTICS I (Credits: 4)

Introduces probability, random variables and their expectations, some commonly used discrete and continuous distributions, concept of random sampling and sampling distributions. Uses computer software packages for simulating, summarizing,
and displaying data.

PREREQUISITE: MTH 229 AND MTH 230, OR EQUIVALENT.

STT 561 APPLIED STATISTICS II (Credits: 4)

Introduces statistics, standard statistical methods for estimation of parameters and hypothesis testing, regression analysis and analysis of variance techniques, and exposure to data analysis using packaged computer programs.

PREREQUISITE: STT 560.

STT 567 INTRODUCTION TO SAS (Credits: 2)

Introduces the use of Statistical Analysis System (SAS), a statistical computing package widely used in industry, government, and academia.

PREREQUISITE: STT 265 OR EQUIVALENT.

STT 586 INDEPENDENT READING IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

Independent reading in statistics and probability.

STT 591 ADVANCED STATISTICAL METHODS FOR NURSIN RESEARCH (Credits: 0.5)

Coverage of concepts, principles, interpretation and practical rules of thumb for advanced statistical methods used in nursing research.

PREREQUISITE: ONE STATISTICS COURSE OR EQUIVALENT.

STT 596 TOPICS IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

May be taken for letter grade or pass/unsatisfactory. Titles vary.

STT 601 NONPARAMETRIC METHODS (Credits: 4)

Distribution-free estimation and hypothesis testing procedures. Includes methods for use in one- and two-sample location and dispersion problems, nonparametric alternatives to ANOVA and regression, goodness-of-fit tests, measures of association, and tests for randomness.

PREREQUISITE: STT 666 OR EQUIVALENT.

STT 611 APPLIED TIME SERIES (Credits: 4)

Stochastic models for discrete time series in the time-domain, moving average processes, autoregressive processes, model identification, parameter estimation, and forecasting. Statistical computing software packages are used.

PREREQUISITE: STT 361/561 OR PERMISSION OF INSTRUCTOR.

STT 624 STATISTICAL QUALITY CONTROL AND IMPROVEMENT (Credits: 4)

Statistical process control for attributes and variables data: probability distributions, sampling plans, control charts, statistical control, process capability, process improvement, tolerance intervals, evolutionary operation, and applications.

PREREQUISITE: STT 361 OR 363 OR PERMISSION OF INSTRUCTOR.

STT 626 RELIABILITY AND LIFE DATA (Credits: 4)

Censoring and truncation, survival and hazard functions, estimation and hypothesis tests, Cox proportional hazards model; diagnostics of the Cox model; state-of-the-art software for survival analysis models.

PREREQUISITE: STT 361 OR EQUIVALENT.
INSTRUCTOR.

STT 628 QUEUEING THEORY (Credits: 4)

The stochastic concept of a queueing process is developed.The theory and applications of single and many server queues are presented.Particular emphasis is placed on application in engineering and computer science.

PREREQUISITE: STT 360 OR STT 363 OR EQUIVALENT.

STT 630 BIOSTATISTICS (Credits: 4)

Statistical methods suitable for analysis of data arising in biological and related studies. Estimation and hypothesis testing are reviewed. Methods include one and two sample tests, simple and multiple regression, and analysis of variance.

PREREQUISITE: STT 265 OR EQUIVALENT OR PERMISSION FROM
THE INSTRUCTOR.

STT 646 STATISTICAL METHODS FOR ENGINEERS I (Credits: 4)

Classical statistical techniques for analysis and interpretation of research data, with extensive use of statistical software. Includes review of basic statistics. Simple, multiple, and polynomial regression, and single
factor analysis of variance are covered.

PREREQUISITE: STT 361 OR 561 OR PERMISSION OF INSTRUCTOR.

STT 647 STATISTICAL METHODS FOR ENGINEERS II (Credits: 4)

Continuation of STT 646. Analysis of variance, techniques for interpretation of research data, with extensive use of statistical software. Includes factoral experiments, fixed and random effects, crossed and nested factors, and repeated measures.

PREREQUISITE: STT 646 OR 466 OR 666.

STT 661 THEORY OF STATISTICS I (Credits: 4)

Probability, random variables, density and distribution functions, expectation, moment generating functions, special discrete and continuous distributions; joint, marginal and conditional distributions; independence, properties of expected values, functions of random variables.

PREREQUISITE: MTH 232 OR PERMISSION OF INSTRUCTOR.

STT 662 THEORY OF STATISTICS II (Credits: 4)

Limiting distributions, central limit theorem, statistics and sampling distributions, point estimation, properties of estimators, sufficiency and completeness, interval estimation, hypothesis testing, most powerful and UMP tests, likelihood ratio tests.

PREREQUISITE: STT 661 OR PERMISSION OF THE INSTRUCTOR.

STT 664 COMPUTATIONAL STATISTICS (Credits: 4)

Bootstrapping is a computing-intensive method of data analysis by computing distributions. The method, including permutation tests, can be easily adapted to many classical problems. Software used for the course includes SPLUS and Mathematica.

PREREQUISITE: STT 560 AND STT 561 OR EQUIVALENT.

STT 666 STATISTICAL METHODS I (Credits: 4)

Classical statistical techniques for analysis and interpretation of research dataincluding the use of statistical software packages. Includes descriptive statistics, one- and two-sample inferences, regression and correlation analysis.

PREREQUISITE: MTH 253, OR 355, AND STT 266 OR STT 361 OR
EQUIVALENT.

STT 667 STATISTICAL METHODS II (Credits: 4)

Continuation of STT 666. Includes analysis of variance, multiple comparisons, analysis of covariance, contingency table analysis, goodness of fit tests.

PREREQUISITE: STT 666.

STT 669 INTRODUCTION TO EXPERIMENTAL DESIGN (Credits: 4)

Randomization, replication, blocking, factoral design. Block designs; multi-factor experiements; fixed-, random-, and mixed-effects models; repeated measures; nested factors; split-plot designs; confounding and fractions for 2**k factorial experiments. Staistical software used extensively.

PREREQUISITE: STT 667 OR PERMISSION OF INSTRUCTOR.

STT 686 INDEPENDENT READING IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

Independent reading in statistics and probability.

STT 696 TOPICS IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

Topics in statistics and probability.

STT 702 APPLIED STOCHASTIC PROCESSES (Credits: 4)

Stationary processes, Markov chains, Poisson processes, pure birth process, queuing processes, inventory problems, and traffic flow problems.

PREREQUISITE: STT 661 OR PERMISSION OF INSTRUCTOR.

STT 706 INTRO TO STATISTICAL MODELING FOR ENVIRONMENTAL DATA (Credits: 4)

Introduction to sampling schemes, exploratory data analysis, probability distributions, and statistical methods for environmental data. Confidence, prediction and tolerance intervals. Introduction to linear models, simulation and risk assessment, and stochastic processes.

PREREQUISITE: STT 561 OR EQUIVALENT.

STT 714 STATISTICAL MODELING FOR ENVIRONMENTAL DATA (Credits: 4)

Statistical techniques for the modeling and analysis of spatial and time-series environmental data, including spatio-temporal analysis, using appropriate software. Applications and case studies.

PREREQUISITE: ES 706 OR STT 706 OR STT 667 OR EQUIVALENT.

STT 721 SAMPLING DESIGN (Credits: 4)

Applications of sampling theory and basic methods of sampling selection. Simple random sampling, systematic sampling, sampling with probability proportionate to unit size, use of auxiliary estimators, and Warner-s procedure.

PREREQUISITE: STT 661 OR PERMISSION OF THE INSTRUCTOR.

STT 740 CONTINGENCY TABLE ANALYSIS (Credits: 4)

Standard techniques for analyzing and describing two-dimensional contingency tables. Logistic regression models and loglinear models developed for data structures involving categorical response variables, including model selection procedures, diagnostics, association graphs, and collapsibility. SAS procedures used for analysis of data sets.

PREREQUISITE: STT 662 AND STT 666, OR PERMISSION OF
INSTRUCTOR.

STT 744 APPLIED MULTIVARIATE ANALYSIS (Credits: 4)

Matrix theory, multivariate distributions, likelihood ratio tests, MANOVA, covariance structure analysis, and classification techniques.

PREREQUISITE: MTH 253 OR MTH 355 AND AT LEAST TWO COURSES
IN PROBABILITY AND STATISTICS OR THE
EQUIVALENT.

STT 761 THEORY OF LINEAR MODELS (Credits: 4)

Concepts of matrix algebra and the multivariate normal distribution are developed in order to study the general linear model of full rank. Some applications of regression are covered.

PREREQUISITE: STT 662 AND MTH 253 AND A STATISTICAL METHODS
COURSE OR PERMISSION OF THE INSTRUCTOR.

STT 762 TOPICS IN LINEAR MODELS (Credits: 4)

Computing techniques and applications of the general linear model. Correlation and regression are emphasized.

PREREQUISITE: STT 761.

STT 764 TOPICS IN EXPERIMENTAL DESIGN (Credits: 4)

Continuation of STT 669. Topics from incomplete block designs, blocked and fractional asymmetric factorial designs, mixture experiments, split-plot designs, response surface methods, parameter design, hierarchical designs, variance components, mixed models.

PREREQUISITE: STT 669 OR PERMISSION OF INSTRUCTOR.

STT 767 APPLIED REGRESSION ANALYSIS (Credits: 4)

Multiple linear regression with introduction to more complicated models, including nonlinear models and up-to-date computing techniques. Completion of a mathematical statistics course or permission of instructor.

PREREQUISITE: STT 666 OR PERMISSION OF INSTRUCTOR.

STT 786 INDEPENDENT READING IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

Independent reading in statistics and probability.

STT 791 STATISTICAL CONSULTING (Credits: 3 TO 4)

Consultation with graduate students and faculty on statistical problems arising from research projects

PREREQUISITE: STT 662, STT 667 AND PERMISSION OF INSTRUCTOR.

STT 796 TOPICS IN STATISTICS AND PROBABILITY (Credits: 1 TO 5)

Topics in statistics and probability.

STT 899 GRADUATE RESEARCH (Credits: 1 TO 18)

Supervised thesis research.