# Graduate Statistics Courses

## Main Content

**Stat 500.** **Applied Statistics. ** (3) Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics. Prerequisite: one undergraduate course in statistics.

**Stat 501.** ** Regression Methods. ** (3) Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; stepwise, piecewise, and logistic regression. Prerequisite: 6 credits of statistics or Stat 500; matrix algebra.

**Stat 502.** ** Analysis of Variance and Design of Experiments. ** (3) Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs. Prerequisite: Stat 462 or Stat 501.

**Stat 503.** ** Design of Experiments. ** (3) Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs. Prerequisites: Stat 502; Stat 462 or Stat 501.

**Stat 504.** ** Analysis of Discrete Data. **(3) Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher-way tables; latent and logistics models. Prerequisites: Stat 460, Stat 502 or Stat 512; matrix algebra.

**Stat 505.** ** Applied Multivariate Statistical Analysis. ** (3) Analysis of multivariate data; T-squared tests; partial correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations. Prerequisites: Stat 501 and Stat 502; matrix algebra.

**Stat 506.** ** Sampling Theory and Methods. ** (3) Theory and application of sampling from finite populations. Prerequisites: calculus; Stat 500 or equivalent.

**Stat 507.** ** Epidemiologic Research Methods. ** (3) Research and quantitative methods for analysis of epidemiologic observational studies. Non-randomized, intervention studies for human health, and disease treatment. Prerequisites: Stat 250 or equivalent.

**Stat 508.** ** Applied Statistical Distribution Theory. ** (3) Analysis of data involving nonnormal families of distributions; model building and selection, parameterizations, inferential algorithms, transformations, simulations, displays, interpretations. Prerequisites: Stat 401.

**Stat 509.** ** Design and Analysis of Clinical Trials.** (3) An introduction to the design and statistical analysis of randomized and observational studies in biomedical research. Prerequisite: Stat 500.

**Stat 510.** ** Applied Time Series Analysis. ** (3) Identification of models for empirical data collected over time. Use of models in forecasting. Prerequisite: Stat 462, 501, or 511.

**Stat 511.** ** Regression Analysis and Modeling. ** (3) Multiple regression methodology using matrix notation; linear, polynomial, and nonlinear models; indicator variables; AOV models; piece-wise regression, autocorrelation; residual analyses. Prerequisites: Stat 500 or equivalent; matrix algebra, calculus.

**Stat 512.** ** Design and Analysis of Experiments. ** (3) AOV, unbalanced, nested factors; CRD, RCBD, Latin squares, split-plot, and repeated measures; incomplete block, fractional factorial, response surface designs; confounding. Prerequisite: Stat 511.

**Stat 513.** ** Theory of Statistics I. ** (3) Probability models, random variables, expectation, generating functions, distribution theory, limit theorems, parametric families, exponential families, sampling distributions. Prerequisite: Math 230.

**Stat 514.** ** Theory of Statistics II. ** (3) Sufficiency, completeness, likelihood, estimation, testing, decision thoery, Bayesian inference, sequential procedures, multivariate distributions and inference, nonparametric inference. Prerequisite: Stat 513.

**Stat 515.** ** Stochastic Processes I. ** (3) Conditional probability and expectation, Markov chains, the exponential distribution and Poisson processes. Prerequisite: Stat (Math) 414 or Stat 513.

**Stat (Math) 516.** ** Stochastic Processes.** (3) Markov chains; generating functions; limit theorems; continuous time and renewal processes; martingales, submartingales, and supermartingales; diffuse processes; applications. Prerequisite: Stat (Math) 416.

**Stat (Math) 517.** ** Probability Theory I ** (3) Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability, special topics. Prerequisite: Math 403.

**Stat (Math) 518.** ** Probability Theory II ** (3) Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability, special topics. Prerequisite: Stat (Math) 517.

**Stat (Math) 519.** ** Topics in Stochastic Processes.** (3) Selected topics in stochastic processes, including Markov and Wiener processes; stochastic integrals, optimal filtering. Prerequisites: Stat (Math) 516, 517.

**Stat 524.** ** Ecometrics. ** (3) Stochastic models and statistical methods in ecological problems; population dynamics, spatial patterns in populations of one, two, or more species. Prerequisite: Stat (Math) 414 or Stat 418.

**Stat 525.** ** Survival Analysis I. ** (3) Location estimation, 2- and k- sample problems, matched pairs, tests for association and covariance analysis when the data are censored. Prerequisites: Stat 512, 514.

**Stat 526.** ** Survival Analysis II. ** (3) Asymptotic theory for Kaplan-Meier estimator, 2- and k- sample rank tests, rank regression, proportional hazards regression. Advanced special topics. Prerequisite: Stat 525.

**Stat (Biol) 527.** ** Quantitative Ecology. ** (3) Introduction to quantitative population and community ecology, with emphasis on problems, concepts, and methods using mathematical, statistical, and computational analysis. Prerequisites: Stat (Math) 409, Biol 210.

**Stat (Biol) 528.** ** Statistical Ecology Spectrum. ** (3) Overview of research and instruction of particular interest to quantitative ecology faculty in the Ecology program. Prerequisite: Stat (Biol) 527.

**Stat 540.** ** Statistical Computing.** (3) Computational foundations of statistics; algorithms for linear and nonlinear models, discrete algorithms in statistics, graphics, missing data, Monte Carlo techniques. Prerequisites: Stat (Math) 415; Stat 501 or 511; matrix algebra.

**Stat 544.** ** Categorical Data Analysis I ** (3) Two-way tables; generalized linear models; logistic and conditional logistic models; loglinear models; fitting strategies; model selection; residual analysis. Prerequisites: Stat 512, 514.

**Stat 545.** ** Categorical Data Analysis II ** (3) Generalized logit modes; symmetry and agreement models; repeated measures; longitudinal data; delta method; asymptotic distributions; ML & WLS; advanced special topics. Prerequisite: Stat 544.

**Stat 548.** ** Statistical Distribution Theory. ** (3) Analytical study of nonnormal models and methods in reliability theory, survival analysis, records evaluation, scale/scale-free analysis, and directional statistics. Prerequisites: Stat (Math) 414, or 416.

**Stat 551.** ** Linear Models I. ** (3) A coordinate-free treatment of the theory of univariate linear models, including multiple regression and analysis of variance models. Prerequisites: Math (Stat) 415 or Stat 514; Stat 512; Math 436 or Math 441.

**Stat 552.** ** Linear Models II. ** (3) Treatment of other normal models, including generalized linear, repeated measures, random effects, mixed, correlation, and some multivariate models. Prerequisite: Stat 551.

**Stat 553. Asymptotic Tools.** (3) Study of large-sample theory without measure theory. Prerequisites: Stat 513-514.

**Stat 561.** ** Statistical Inference I. ** (3) Classical optimal hypothesis test and confidence regions, Bayesian inference, Bayesian computation, large sample relationship between Bayesian and classical procedures. Prerequiste: Stat 514.

**Stat 562.** ** Statistical Inference II ** (3) Basic limit theorems; asymptotically efficient estimators and tests; local asymptotic analysis; estimating equations and generalized linear models. Prerequisite: Stat 561.

**Stat 564.** ** Theory of Nonparametric Statistics.** (3) Estimation and testing based on nonparametric procedures for location and regression models. Distribution theory and asymptotic efficiency. Prerequisites: Stat (Math) 415 or Stat 514.

**Stat 565.** ** Multivariate Analysis.** (3) Theoretical treatment of methods for analyzing multivariate data, including Hotelling's T-squared, MANOVA, discrimination, principal components, and canonical analysis. Prerequisites: Stat 505, 551.

**Stat 572.** ** Statistical Decision Theory I. ** (3) Structure of statistical games, optimal strategies, fixed sample-size games. Prerequisite: Stat (Math) 415 or Stat 514.

**Stat 580.** ** Statistical Consulting Practicum I. ** (2) General principals of statistical consulting and statistical consulting experience. Preparation of reports, presentations, and communication aspects of consulting are discussed. Prerequisites: Stat 502; Stat 503, 504, or 506.

**Stat 581.** ** Statistical Consulting Practicum II. ** (1) Statistical consulting experience including client meetings, development of recommendation reports, and discussion of consulting solutions. Prerequisites: Stat 580.

**Stat 590.** ** Colloquium** (1-3)

**Stat 596.** ** Individual Studies **(1-9)

**Stat 597.** ** Special Topics ** (1-9)