146 / FIELDS OF INSTRUCTION commonly used sampling techniques; simple random sam- ple, cluster, ratio, regression, stratified, multistage, and sys- tematic samples. Special topics include wildlife surveys, non-sampling error adjustment, categorical data analysis, and practical survey examples. STA 6246-Theory of Least Squares (3) Prereq: STA 6207. Theory underlying general linear models, parameter esti- mation, and hypothesis testing in full rank and less than full rank models, use of residuals in regression analysis, ill-condi- tioned problems, biased estimation, variable screening pro- cedures. STA 6247-Advanced Topics in Design and Analysis (3) Pre- req: STA 6246, 6207-6208. General rules of analysis of vari- ance pertaining to balanced linear classification models. Pro- cedures of estimation and hypothesis testing for unbalanced data. Estimation of variance components. Response surfaces for first and second order linear models. Biased estimation procedure and mixture experiments. STA 6267-Sequential Methods (3) Prereq: STA 6327. Double sampling procedures, the sequential probability ratio tests, sequential tests for composite hypotheses, sequential esti- mation and confidence intervals. STA 6326-Introduction to Theoretical Statistics I (3) Prereq: MAC 3314. Theory of probability. Probability spaces, con- tinuous and discrete distributions, functions of random vari- ables, multivariate distributions, expectation, conditional expectation, central limit theorem, useful convergence re- sults, sampling distributions, distributions of order statistics, empirical distribution function. STA 6327-Introduction to Theoretical Statistics II (3) Pre- req: STA 6326. Estimation and hypothesis testing. Sufficiency, information, estimation, maximum likelihood, confidence intervals, uniformly most powerful tests, likelihood ratio tests, sequential testing, univariate normal inference, de- cision theory, analysis of categorical data. STA 6466-Probability Theory I (4) Prereq: MAA 5226 or equivalent. Measure and probability spaces; random vari- ables; distribution functions; abstract Lebesgue and Lebesgue-Stieltjes integration; monotone, dominated, Cau- chy, and mean convergence; Fubini and Radon-Nikodym theorems; zero-one laws. STA 6467-Probability Theory II (4) Prereq: STA 6466. Sum- mability of independent random variables, laws of large numbers, convergence in distribution, characteristic func- tions, uniqueness and continuity theorems, the Lindeberg- Feller central limit theorem, degenerate convergence criterion. STA 6505-Analysis of Categorical Data (3) Prereq: STA 6327 and 6207 or consent of instructor. Varieties of categorical data, cross-classification tables, tests for independence. Measures of association. Loglinear models for multi- dimensional tables. Logit models and analogies with regres- sion. Specialized methods for ordinal data. STA 6526-Nonparametric Statistics (3) Prereq: STA 6327 or consent of instructor. Inference based on rank statistics- one, two and k-sample problems, correlation and regression probleins and analysis of contingency tables. Conditionally distribution-free rank tests. Pitman asymptotic relative effi- ciency. STA 6706-Applied Multivariate Methods for Behavioral Re- search (3) Prereq: STA 6166 or consent of instructor. Bivariate relationship: matrix algebra; review of multiple regression and correlation; part and partial correlation; canonical cor- relation; discriminant analysis and classification; cluster analysis; factor analysis.' STA 6707-Analysis of Multivariate Data (3) Prereq: STA 6208 or consent of instructor. Standard methodology in pro- cessing multivariate data including an introduction to the following topics; cluster analysis, discriminant analysis, fac- tor analysis and principal components. Classical tests on the mean and dispersion matrices are given. STA 6746-Multivariate Analysis (4) Prereq: STA 6246. The multivariate normal, Wishart and generalized beta distribu- tions. Likelihood tests of hypothesis concerning the mean and dispersion matrices. The u-statistic. STA 6826-Stochastic Processes I (3) Prereq: STA 6327. Dis- crete time and state Markov process. Ergodic theory. STA 6827-Stochastic Processes 11 (4) Prereq: STA 6826. Con- tinuous time Markov processes. The Poisson and allied pro- cesses. The Kolmogorov equations. Renewal theory. STA 6857-Applied Time Series Analysis (3) Prereq: STA 4322 and a basic computer language. Linear time series model building, spectral density estimation, analysis of nonsta- tionary data, SAS package on Box and Jenkins model build- ing and forecasting. Case studies in recent literature will be discussed. STA 6876-Theory of Time Series (3) Prereq: STA 6327. Foun- dations of stationary time series, distributions of sample au- tocorrelations, partial autocorrelation, spectral density, time series regression, and special topics in recent time series re- search. STA 6900-Problems in Statistics (1-4; max: 6) Prereq: per- mission of department. Special problems in research meth- ods, sampling methods, and experimental designs. STA 6905-Individual Work (1-4; max: 10) Prereq: permission of department. Special topics designed to meet the needs and interests of individual students. STA 6910-Supervised Research (1-5; max: 5) S/U. STA 6934-Special Topics in Statistics (1-3; max: 8) Prereq: permission of graduate adviser. STA 6937-Seminar: Current Topics in Statistics (1-3; max: 6) Prereq: permission of department. Discussion of current re- search topics in statistics not covered in regular courses. S/U. STA 6938-Seminar (1) Prereq: permission of department. Special topics of an advanced nature suitable for seminar treatment but not given in regular courses. S/U. STA 6940-Supervised Teaching (1-5; max: 5) S/U. STA 6971-Research for Master's Thesis (1-15) S/U. STA 7346--Statistical Inference I (4) Prereq: STA 6327. De- cision rules and risk functions. Sufficiency, Minimax, and Bayes rules for estimation of location and scale parameters. STA 7347-Statistical Inference II (4) Prereq: STA 7346. Bayesian statistical inference. Inference using large samples. Relative efficiencies of tests and estimates with special refer- ence to Pitman and Bahadur efficiencies. STA 7979-Advanced Research (1-9) Research for doctoral students before admission to candidacy. Designed for stu- dents with a master's degree in the field of study or for stu- dents who have been accepted for a doctoral program. Not open to students who have been admitted to candidacy. S/U. STA 7980-Research for Doctoral Dissertation (1-15) S/U. SUBJECT SPECIALIZATION TEACHER EDUCATION College of Education GRADUATE FACULTY 1984-85 Chairman: E. A. Todd. Graduate Coordinator: E. J. Bolduc, Jr. Professors: E. J. Bolduc, Jr.; G. D. Carr; J. D. Casteel; J. W. Gregory; C. L. Hallman; E. L. Kantowski; J. J. Koran, Jr.; V. McGuire; M. B. Rowe; E. A. Todd. As- sociate Professors: D. H. Bernard; R. C. Ferguson; M. E. Flannery; C. A. Henderson; A. P. Newcomb, Jr.; R. G. Wright. Assistant Professor: M. E. Timmerman. The Department of Subject Specialization Teacher Education is composed of the following special- izations: art education, business education, English education, foreign language education, mathematics education, music education, science education, and social studies education. The Department offers the Master of Education (nonthesis) and the Master of Arts in Education (thesis) degrees with an emphasis in teaching at any level of education. Advanced graduate degrees, Ed.S., Ed.D., and Ph.D., are offered in curriculum and in- struction. Beyond the Graduate School requirements, begin- ning graduate students should have appropriate un- dergraduate training in professional education and in a field of subject specialization. Each graduate stu- dent is counseled during the first semester to develop