Course Descriptions STA 644 ADVANCED LINEAR AND NONLINEAR MODELS. (3) Review of the general linear model. Regression methodology using Ridge, Bayes, and Stein estimaters. The use of PRESS, Cp, and R2 statistics as selection criteria. Modern computational methods. Nonlinear models and their methodology. Robust Regression. Prereq: STA 603. STA 653 CLINICAL TRIALS. (3) Design and analysis of Phase I-III clinical trials, interim monitoring of trials, sample size, power, crossover trials, bioequivalency, mixed models, and meta analysis. Coreq: STA 603. (Same as BST 713.) STA 655 INTRODUCTION TO STATISTICAL GENETICS. (3) BST 655 presents an introduction to the statistical methodologies used today to investigate genetic susceptibility to complex diseases. The course focuses on linkage and association analysis with applications to real-world data. Commonly used (and freely available) software will be presented and used throughout. Because the field is constantly evolving, a focus of the material for this course will be recent statistical human genetics literature. Prereq: STA 580 or equivalent. (Same as BST 655.) STA 661 MULTIVARIATE ANALYSIS I. (3) Characterization and properties of the multivariate normal distribution, random samples from this distribution; multivariate analysis of variance, related distribution theory; factor analysis. Prereq: STA 603. STA 662 RESAMPLING AND RELATED METHODS. (3) Theory and application of the bootstrap, jackknife and other resampling methods. Prereq: STA 605 and STA 606. STA 665 ANALYSIS OF CATEGORICAL DATA. (3) Multinomial and product-multinomial models; large-sample theory of estimation and testing, Pearson chi-square and modified chi-square statistics, Pearson-Fisher Theorem, Wald Statistics and generalized least squares technique; applications to problems of symmetry, association and hypotheses of no interaction in multi-dimensional contingency tables. Prereq: STA 603 and STA 606. (Same as BST 763.) STA 671 REGRESSION AND CORRELATION. (2) Simple linear regression, elementary matrix algebra and its application to simple linear regression; general linear model, multiple regression, analysis of variance tables, testing of subhypotheses, nonlinear regression, step-wise regression; partial and multiple correlation. Emphasis upon use of computer library routines; other special topics according to the interests of the class. Lecture, three hours per week; laboratory, two hours per week for seven and one half weeks. Offered the first or second half of each semester. Prereq: STA 570 or STA 580. STA 672 DESIGN AND ANALYSIS OF EXPERIMENTS. (2) Review of one-way analysis of variance; planned and unplanned individual comparisons, including contrasts and orthogonal polynomials; factorial experiments; completely randomized, randomized block, Latin square, and split-plot designs: relative efficiency, expected mean squares; multiple regression analysis for balanced and unbalanced experiments, analysis of covariance. Lecture, three hours per week; laboratory, two hours per week for seven and a half weeks. Offered the first or second half of each semester. Prereq: STA 671. STA 679 DESIGN AND ANALYSIS OF EXPERIMENTS II. (3) A continuation of STA 672. Multiplicative models in two-factor experiments. Partial factorials. Extensions and modifications of split plots and Latin squares. Confounding in factorial experiments. Response surface methods. Estimation of variance components. One restrictional and two restrictional lattice and incomplete block designs. Combining analyses of similar experiments. Prereq: STA 671 and 672 or equivalent. STA 681 BIOSTATISTICS II. (3) Students will learn statistical methods used in public health studies. This includes receiver operator curves, multiple regression logistic regression, confounding and stratification, the Mantel-Haenzel procedure, and the Cox proportional hazardous model. Lecture, two hours; laboratory, two hours per week. Prereq: STA 580 or equivalent. (Same as SPH 630.) STA 690 SEMINAR IN STATISTICS. May be repeated to a maximum of three credits. (1) STA 692 STATISTICAL CONSULTING. (3) Basic principles of statistical consulting including how to manage a consulting session, how to formulate and solve problems and how to express results both orally and in writing. Students will be expected to analyze data from a current consulting project. Lecture, two hours; laboratory, two hours per week. Coreq: STA 643 or 644 or consent of instructor. STA 693 BIOSTATISTICAL PRACTICUM. (1-2) This course will involve students in small consulting projects intended to illustrate practical biostatistical problems. Prereq: STA 603. STA 695 SPECIAL TOPICS IN STATISTICAL THEORY (Subtitle required). (1-3) To be selected by staff. May be repeated to a maximum of nine credits. Prereq: STA 601. STA 700 FOUNDATIONS OF PROBABILITY AND INFERENCE. (3) Measures on the real line and probability spaces, Lebesque measure, properties of distribution functions and random variables, integrals and expectations. Prereq: MA 471G. STA 701 ADVANCED STATISTICAL INFERENCE I. (3) Basic concepts of decision theory, sufficiency and completeness; completeness of multiparametric exponential family; unbiasedness and invariance of decision rules; Bayes, minimax and invariant estimators; testing of hypotheses and optimality properties. Prereq: STA 607 and STA 700. STA 702 ADVANCED STATISTICAL INFERENCE II. (3) UMP and UMP unbiased tests for multiparametric exponential families; locally best tests; invariance and permutation tests, UMP invariant tests for linear hypotheses; asymptotic aspects of classical statistics, ML estimation and concepts of efficiency; sequential probability ratio test; confidence set, UMA unbiased and invariance confidence sets. Prereq: STA 701. STA 703 ADVANCED PROBABILITY. (3) Probability spaces, extension theorem, random variables; independence, conditional probability, conditional expectation; laws of large numbers, law of the iterated logarithm; convergence in distribution; characteristic functions; central limit theorems; martingales. Prereq: STA 700 and STA 532. STA 673 DISTRIBUTION-FREE STATISTICAL INFERENCEANDANALYSISOFCATEGORICALDATA. (2) Inference for population quantiles, sign tests, Wilcoxon tests, Kruskal-Wallis and Friedman tests, Kendall and Spearman rank correlation. Goodness-of-fit tests for completely and partially specified distributions, rxc contingency tables, McNemar and Cochran’s Q tests for matched proportions; three dimensional tables and tests of partial and multiple associations. Lecture, three hours per week; laboratory, two hours per week for seven and a half weeks. Offered the first or second half of each semester. Prereq: STA 570 or STA 580. STA 704 ADVANCED PROBABILITY - STOCHASTIC PROCESSES. (3) Random functions; jump Markov processes; processes with independent increments; stationary stochastic processes; diffusion processes; limit theorems; applications of stochastic processes. Prereq: STA 703. STA 675 SURVEY SAMPLING. (2) Simple random sampling and stratified random sampling, ratio and regression estimators, cluster sampling, systemic sampling, and multi-stage sampling. Specific problems associated with running a survey: non-response, call-backs, questionnaire construction, mail questionnaires, and area sampling. Lecture, three hours per week; laboratory, two hours per week for seven and a half weeks. Offered the first or second half of each semester. Prereq: STA 570 or STA 580. STA 707 ADVANCED DATA ANALYSIS. (3) Theory and data analysis involving likelihood functions, mixed models, missing responses. Prereq: STA 643. STA 676 QUANTITATIVE INHERITANCE IN PLANT POPULATIONS. (3) After a brief review of population genetics theory, the course is divided into two sections which cover methods of estimating genetic variances and selection methods in population improvement. The course will focus on handling and interpretation of actual data sets through data analysis and discussion of current literature. Prereq: STA 570, STA 671, and STA 672. (Same as PLS 676.) STA 677 APPLIED MULTIVARIATE METHODS. (3) Survey of multivariate statistical techniques. The multivariate normal distribution; the general linear model; general procedures for parameter estimation and hypothesis testing in the multivariate case; Hotelling’s T2, multivariate analysis of variance and covariance; structural models for the covariance matrix; utilization of existing computer programs. Prereq: STA 671 and 672. University of Kentucky KEY: # = new course STA 705 ADVANCED COMPUTATIONAL INFERENCE. (3) Numerical maximization and integration, resampling methods, EM algorithm, Markov Chain Monte Carlo methods. Prereq: STA 605 and STA 701. STA 709 ADVANCED SURVIVAL ANALYSIS. (3) Lindberg CLT, Kaplan-Meier and related estimators, Cox proportional hazards and related methods, approximations of type I and II error. Prereq: STA 635, 701. STA 715 READINGS IN STATISTICS AND PROBABILITY (Subtitle required). (1-6) Supervised reading and discussion of a selected research topic. May be repeated to a maximum of nine credits. Prereq: STA 701 and STA 703 and consent of instructor. STA 748 MASTER’S THESIS RESEARCH. (0) Half-time to full-time work on thesis. May be repeated to a maximum of six semesters. Prereq: All course work toward the degree must be completed. STA 749 DISSERTATION RESEARCH. (0) Half-time to full-time work on dissertation. May be repeated to a maximum of six semesters. Prereq: Registration for two full-time semesters of 769 residence credit following the successful completion of the qualifying exams. STA 767 DISSERTATION RESIDENCY CREDIT. (2) Residency credit for dissertation research after the qualifying examination. Students may register for this course in the semester of the qualifying examination. A minimum of two semesters are required as well as continuous enrollment (Fall and Spring) until the dissertation is completed and defended. 2013-2014 Undergraduate Bulletin * = course changed † = course dropped 587 *