STAT - Statistics

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

STAT 150 Introduction to Statistics

Stat 150 Introduction to Statistics (3 cr)

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 204 Special Topics

STAT 251 Statistical Methods

Stat 251 Statistical Methods (3 cr)

Gen Ed: Mathematics

Credit not awarded for Stat 251 after Stat 301 or Stat 416, or for Stat 416 after Stat 251 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: One of the following: Math 108, Math 137, Math 143, Math 160, Math 170, or Sufficient score on SAT, ACT, or math placement test (see www.uidaho.edu/registrar/registration/placement).

STAT 299 Directed Study

STAT 301 Probability and Statistics

Stat 301 Probability and Statistics (3 cr)

Credit not awarded for Stat 251 after Stat 301 or Stat 416, or for Stat 416 after Stat 251 or Stat 301. 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 404 Special Topics

STAT 416 Statistical Methods for Research

Stat 416 Statistical Methods for Research (3 cr)

Credit not awarded for Stat 251 after Stat 301 or Stat 416, or for Stat 416 after Stat 251 or Stat 301. 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: One of the following: Math 108, Math 137, Math 143, Math 160, Math 170, or Sufficient score on SAT, ACT, or math placement test (see www.uidaho.edu/registrar/registration/placement).

STAT 419 Introduction to SAS/R Programming

Stat 419 Introduction to SAS/R Programming (3 cr)

An introduction to the SAS and R programming languages. Topics include creating data, importing data, accessing subsets of data, exporting data, plotting and graphing, loops and functions. Course provides a basic knowledge of SAS and R to help students master statistical tools available in SAS and R, including basic statistical analyses.

Prereq: Stat 251, 301, or 416

STAT 422 Survey Sampling Methods

Stat 422 Sample Survey Methods (3 cr)

Introduction to survey sampling designs and inference including simple, stratified, and cluster sampling; ratio and regression estimators, unequal probability sampling, and population size estimation. Cooperative: open to WSU degree-seeking students.

Prereq: Stat 251 or Stat 301 or Stat 416

STAT 426 SAS Programming

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 or Stat 416

STAT 428 Geostatistics

Stat 428 Geostatistics (3 cr)

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

STAT 431 Statistical Analysis

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

Stat 433 Econometrics (3 cr)

See Econ 453.

STAT 446 Six Sigma Innovation

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

Stat 451 Probability Theory (3 cr)

See Math 451.

STAT 452 Mathematical Statistics

Stat 452 Mathematical Statistics (3 cr)

See Math 452.

STAT 453 Stochastic Models

Stat J453/J544 Stochastic Models (3 cr)

See Math J453/J538.

STAT 456 Quality Management

Stat 456 Quality Management (3 cr)

See OM 456.

STAT 498 Internship

Stat 498 (s) Internship (cr arr)
Prereq: Permission

STAT 499 Directed Study

Stat 499 (s) Directed Study (cr arr)

STAT 500 Master's Research and Thesis

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

STAT 501 Seminar

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 Directed Study

Stat 502 (s) Directed Study (cr arr)

STAT 503 Workshop

Stat 503 (s) Workshop (cr arr)

STAT 504 Special Topics

Stat 504 (s) Special Topics (cr arr)

STAT 507 Experimental Design

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 514 Nonparametric Statistics

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

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

517 Statistical Learning and Predictive Modeling

STAT 517 Statistical Learning and Predictive Modeling (3 cr)

A comprehensive overview of statistical learning and predictive modeling techniques to analyze large data sets in science, social science, and other data-rich fields including, for example, biology, business, and engineering. Topics include regression, classification, resampling methods, model selection and regularization, tree-based methods, support vector machines, clustering, and text mining. The implementation of the methods will be in R, and Python as needed. Basic experience with computer programming is assumed.

Prereq: STAT 431

STAT 519 Multivariate Analysis

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 525 Master's Econometrics

Stat 525 Master's Econometrics (3 cr).

See AgEc 525.

STAT 544 Stochastic Models

Stat J453/J544 Stochastic Models (3 cr)

See Math J453/J538.

STAT 550 Regression

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

Stat 555 Statistical Ecology (3 cr)

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

STAT 565 Computer Intensive Statistics

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

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 Consulting Practicum

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 Internship

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 Research

Stat 599 (s) Non-thesis Master's Research (cr arr)

Research not directly related to a thesis or dissertation.

Prereq: Permission