STAT 700 - Applied Statistics I (3 Credits)
Introduction to probability and the concepts of estimation and hypothesis testing for use in experimental, social, and professional sciences. One and two-sample analyses, nonparametric tests, contingency tables, sample surveys, simple linear regression, various statistical packages. Not to be used for M.S. or Ph.D. credit in statistics or mathematics. Not to be used for M.S. or Ph.D. credit in statistics or mathematics.
Introduction to probability and the concepts of estimation and hypothesis testing for use in experimental, social, and professional sciences. One and two-sample analyses, nonparametric tests, contingency tables, sample surveys, simple linear regression, various statistical packages. Not to be used for M.S. or Ph.D. credit in statistics or mathematics. Not to be used for M.S. or Ph.D. credit in statistics or mathematics.
STAT 701 - Applied Statistics II (3 Credits)
Continuation of STAT 700. Simple linear regression, correlation, multiple regression, fixed and random effects analysis of variance, analysis of covariance, experimental designs, some multivariate methods, various statistical packages. Not to be used for M.S. or Ph.D. credit in statistics or mathematics.
Prerequisites: STAT 700 or the equivalent.
STAT 702 - Introduction to Statistical Theory I (3 Credits)
Fundamental theory of statistics and how it applies to industrial problems. Topics include probability, random variables and vectors and their distributions, sampling theory, point and interval estimators, and application to the theory of reliability, regression, process control and quality issues. Not to be used for M.S. or Ph.D. credit in statistics.
Prerequisites: MATH 142.
Fundamental theory of statistics and how it applies to industrial problems. Topics include probability, random variables and vectors and their distributions, sampling theory, point and interval estimators, and application to the theory of reliability, regression, process control and quality issues. Not to be used for M.S. or Ph.D. credit in statistics.
Prerequisites: MATH 142.
STAT 703 - Introduction to Statistical Theory II (3 Credits)
Continuation of STAT 702. Topics include discussion of theoretical properties of point estimators and tests of hypotheses, elements of statistical tests, the Neyman-Pearson Lemma, UMP tests, likelihood ratio and other types of tests, and Bayes procedures in the decision process. Not to be used for M.S. or Ph.D. credit in statistics.
Prerequisites: STAT 702.
STAT 704 - Data Analysis I (3 Credits)
Primarily for graduate students in statistics and the mathematical sciences. Probability concepts, inferences for normal parameters, regression, correlation, use of computer statistical packages.
Prerequisite or Corequisite: STAT 712.
STAT 705 - Data Analysis II (3 Credits)
Continuation of STAT 704. Analysis of variance (fixed and random effects), analysis of covariance, experimental design, model building, other applied topics, and use of computer statistical packages.
Prerequisites: STAT 704 and STAT 712.
STAT 706 - Experimental Design (3 Credits)
Specialized experimental design: 2n and 3n factorials; fractional replication; confounding; incomplete block designs, including split-plot, split-block, and Latin square designs; general principles of design.
Prerequisites: STAT 701 or STAT 705.
STAT 708 - Environmetrics (3 Credits)
Statistical methods for environmental and ecological sciences, including nonlinear regression, generalized linear models, spatial analyses/kriging, temporal analyses, meta-analysis, quantitative risk assessment.
Prerequisites: STAT 701 or STAT 705 or BIOS 757.
STAT 709 - Environmetrics II (3 Credits)
Theoretical underpinnings of environmetrics. Spatial statistics, temporal and longitudinal analysis, hierarchical modeling, and Bayesian inferences for environmental data.
Prerequisites: STAT 708 or BIOS 808; STAT 714.
STAT 712 - Mathematical Statistics I (3 Credits)
Sample spaces, probability and conditional probability, independence, random variables, expectation, distribution theory, sampling distributions, laws of large numbers and asymptotic theory, order statistics, and estimation.
Prerequisites: advanced calculus.
STAT 713 - Mathematical Statistics II (3 Credits)
Further development of estimation theory and tests of hypotheses, including an introduction to Bayes estimation, sufficiency, minimum variance principles, uniformly most powerful and likelihood ratio tests, and sequential probability ratio tests.
Prerequisites: STAT 712.
STAT 714 - Linear Statistical Models (3 Credits)
A study of the general linear statistical model and the linear hypothesis. Topics include the multivariate normal distribution, distributions of quadratic forms, and parameter estimation and hypothesis testing for full-rank models, regression models, and less than full-rank models.
Prerequisites: STAT 513 and MATH 544 or STAT 712 or equivalent.
STAT 714 - Linear Statistical Models (3 Credits)
A study of the general linear statistical model and the linear hypothesis. Topics include the multivariate normal distribution, distributions of quadratic forms, and parameter estimation and hypothesis testing for full-rank models, regression models, and less than full-rank models.
Prerequisites: STAT 513 and MATH 544 or STAT 712 or equivalent.
STAT 715 - Nonlinear Statistical Models (3 Credits)
Inference for general nonlinear parametric statistical models for univariate and multivariate response; linear and quadratic estimating equations; models for covariance structure; effects of model misspecification and robustness.
Prerequisites: STAT 713, STAT 714.
STAT 716 - Selected Topics in Probability (1-3 Credits)
Special topics in probability theory and stochastic processes not offered in other courses.
STAT 718 - Selected Topics in Statistics (1-3 Credits)
Special topics in statistics not offered in other courses.
STAT 720 - Times Series Analysis (3 Credits)
Stochastic properties, identification, estimation, and forecasting methods for stationary and nonstationary time series models.
Prerequisites: STAT 704 and STAT 512.
STAT 721 - Stochastic Processes (3 Credits)
Theory of stochastic processes, including branching processes, discrete and continuous time Markov chains, renewal theory, point processes, and Brownian motion.
Prerequisites: STAT 711 or STAT 712.
STAT 730 - Multivariate Analysis (3 Credits)
A survey of the theory and applications of the fundamental techniques for analyzing multivariate data.
Prerequisites: STAT 713.
STAT 740 - Statistical Computing (3 Credits)
A survey of current algorithms and software for solving fundamental problems of statistical computing with emphasis on computer generation of random variates.
Prerequisites: STAT 713 and knowledge of a computer programming language.
STAT 750 - Response Surface Methodology (3 Credits)
Methods for fitting (regression) response surfaces and interpreting them subject to random error. Includes designs and industrial process optimization methods.
Prerequisites: STAT 701 or STAT 705.
STAT 761 - Reliability and Life Testing (3 Credits)
The various statistical and probability models in reliability and life testing and inference procedures for such models, including life distributions, parametric and nonparametric inference methods, hazard and failure rate functions, plotting methods, analysis of mixtures, censoring.
Prerequisites: STAT 703 or STAT 713.
STAT 770 - Categorical Data Analysis (3 Credits)
Advanced methods for analysis of discrete data. Higher-order contingency tables, log-linear and other generalized linear models. Multivariate methods for matched pairs and longitudinal data.
Prerequisites: STAT 704 or BIOS 759.
STAT 771 - Applied Longitudinal Data Analysis (3 Credits)
Modern methods for the analysis of repeated measures, correlated outcomes, and longitudinal data, including repeated measures ANOVA, generalized linear models, random effects, and generalized estimating equations.
Prerequisites: BIOS 757 or BIOS 758 or STAT 701 or STAT 705.
Cross-listed course: BIOS 770
Cross-listed course: BIOS 770
STAT 775 - Generalized Linear Models (3 Credits)
Statistical theory and applications extending regression and analysis of variance to non-normal data. Encompasses logistic and other binary regressions, log-linear models, and gamma regression models.
Prerequisites: STAT 713 or STAT 513, and STAT 705 or BIOS 757.
Cross-listed course: BIOS 815
Cross-listed course: BIOS 815
STAT 778 - Item Response Theory (3 Credits)
Statistical models for item response theory, Rasch and other models for binary and polytomous data, and applications. Use of statistical software.
Prerequisites: EDRM 711 or PSYC 710 or STAT 701 or STAT 704.
Cross-listed course: EDRM 828
Cross-listed course: EDRM 828
STAT 790 - Seminar in Statistical Consulting (1 Credit)
An exposure to the techniques of statistical consulting through discussion and analysis of actual statistical problems which occur in fields of application.
Prerequisites: STAT 700 or equivalent.
STAT 791 - Practicum in Statistical Consulting (1 Credit)
Experiences in actual statistical consulting settings; participation and critiques.
Prerequisites: STAT 790.
STAT 798 - Independent Study (1-6 Credits)
STAT 799 - Thesis Preparation (1-9 Credits)
CL: 2020.
CL: 2020.
STAT 810 - Probability Theory I (3 Credits)
Probability spaces, random variables and distributions, expectations, characteristic functions, laws of large numbers, and the central limit theorem.
Prerequisites: STAT 511, STAT 512, or MATH 703.
Cross-listed course: MATH 710
Cross-listed course: MATH 710
STAT 811 - Probability Theory II (3 Credits)
More about distributions, limit theorems, Poisson approximations, conditioning, martingales, and random walks.
Cross-listed course: MATH 711
STAT 822 - Advanced Statistical Inference (3 Credits)
The advanced theory of statistical inference, including the general decision problem; Neyman-Pearson theory of testing hypotheses; the monotone likelihood ratio property; unbiasedness, efficiency, and other small sample properties of estimators; asymptotic properties of estimators, especially maximum likelihood estimators; and general sequential procedures.
Prerequisites: STAT 713.
STAT 823 - Large Sample Theory (3 Credits)
Modes of convergence, limit theorems, and the asymptopic properties of estimators and tests.
Prerequisites: STAT 713.
STAT 824 - Nonparametric Inference (3 Credits)
The general theory of nonparametric statistics, including order statistic theory, theory of ranks, U-statistics in nonparametric estimation and testing, linear rank statistics and their application to location and scale problems, goodness-of-fit, and other distribution-free procedures.
Prerequisites: STAT 713.
STAT 890 - Doctoral Seminar (3 Credits)
For doctoral candidates.
STAT 898 - Directed Readings and Research (1-12 Credits)
CL: 2020.
STAT 899 - Dissertation Preparation (1-12 Credits)
For doctoral candidates.