Graduate Course Descriptions
STA 5223Applied Sample Survey Methods
(Fall in even numbered years)


Credits: 3

Prereq: STA 2023 or STA 4322 or STA 5328 or STA
6126 or STA 6166

Design and analysis of sample surveys. Sources
of error; questionaire design; simple random, stratified, systematic,
and cluster sampling; plus practical application of these concepts.

STA 5325Mathematical Methods of Statistics
(Fall, Spring, Summer)


Credits: 3

Prereq: MAC 2313 and Intro. Stat.

Probability, counting rules, conditional
probablity, independence, Bayes' Rule. Discrete and continuous
distributions, means, variances, moment generating functions.
Multivariate probability distributions, marginal and conditional
distributions, covariance. Distributions of functions of random
variables.

STA 5328Mathematical Methods of Statistics
II (Fall, Spring, Summer)


Credits: 3

Prereq: STA 4321 or STA 5325

Mathematical foundations of point estimation,
confidence intervals, tests of hypotheses, linear models and analysis
of variance.

STA 5503Categorical Data Methods (Spring)


Credits: 3

Prereq: STA 3024 or STA 3032 or STA 4210 or STA
4322 or STA 6127 or STA 6167

Intended for graduate students not majoring in
statistics. Description and inference using proportions and odds
ratios, multiway contingency tables, logistic regression and other
generalized linear models, and loglinear models applications.

STA 5507Applied Nonparametric Methods
(Fall in odd numbered years)


Credits: 3

Prereq: STA 2023 or STA 3032 or STA 4210 or STA
4322 or STA 6126 or STA 6166

Introduction to nonparametric statistics,
including one and two sample testing and estimation methods, one and
twoway layout models, and correlation and regression models.

STA 5701Applied Multivariate Methods
(Spring in odd numbered years)


Credits: 3

Prereq: STA 3024 or STA 4210 or STA 4322 or STA 6127 or STA 6166 
Review of matrix theory, univariate normal, t,
chisquared, F and multivariate normal distributions. Inference about
multivariate means including Hotelling's T squared, multivariate
analysis of variance, multivariate regression and multivariate repeated
measures. Inference about covariance structure including principal
components, factor analysis and cannonical correlation. Multivariate
classification techniques including discriminant and cluster analysis.
Additional topics at the discretion of the instructor, time permitting.

STA 5823Stochastic Process Methods (Fall
in even numbered years)


Credits: 3

Prereq: STA 4321 or STA 5325

Mathematical foundations of elementary
stochastic processes; Poisson processes; Markov chains; branching and
renewal processes.

STA 6092Applied Statistical Practice (See
Schedule of Graduate Major Course Offerings)


Credits: 3

Prereq: STA 6207 and STA 6208

Introduction to communication, management,
organizational, computational, and statistical thinking skills
necessary to consulting in statistics. Integration of graphical and
numerical computing tools, research design concepts, data summary and
statistical inference methods.

STA 6126 Statistical Methods in Social
Research I (Fall, Spring)


Credits: 3

Prereq: None

Descriptive statistics, estimation,
significance tests, twosample comparisons, methods for nominal and
ordinal data, regression and correlation, introduction to multiple
regression.

STA 6127Statistical Methods in Social
Research II (Spring)


Credits: 3

Prereq: STA 6126

Further topics in multiple regression, model
building, analysis of variance, analysis of covariance, multivariate
analysis of categorical data.

STA 6166Statistical Methods in Research I
(Fall, Spring, Summer A)


Credits: 3

Prereq: None

Statistical inference based on t, F, and X2
tests. Analysis of variance for basic experimental designs. Factorial
experiments. Regression analysis and analysis of covariance.

STA 6167Statistical Methods in Research II
(Spring, Summer B)


Credits: 3

Prereq: STA 6166

Analysis of splitplot and nested designs with
incomplete blocks, confounding and fractional replications. Analysis of
count data. Nonparametric methods.

STA 6176Introduction to Biostatistics
(Spring)


Credits: 3

Prereq: STA 6207 and STA 6326

Analysis of epidemiological studies, measures
of morbidity and mortality, methods for rates and proportions,
bioassay, longitudinal data analysis.

STA 6177Survival Analysis and Clinical
Trials (Fall)


Credits: 3

Prereq: STA 6327

Survival analysis, KaplanMeier estimates,
proportional hazards model, related tests, phase I, II, and III
clinical trials, designs and protocols.

Credits: 3

Prereq: STA 6327

Biological and molecular basis. Likelihood
ratio test, multinomial distribution and Bailey's theorem. Linkage
analysis of qualitative traits. Twin and sibling studies. Computation
of kinship coefficient by matrix method. Mapping of quantitative trait
loci by EM algorithm. Heritability. Breeding value predication using
flanking markers with variance component analysis. Linkage
disequilibrium analysis for gene mapping. Forensic genetics using
Bayes' formula. Genetic counseling. Gene pattern matching and
construction of evolutionary trees by cluster analysis.

STA 6200Fundamental of Research Design
(Fall)


Credits: 2

Prereq: None

Choosing the research objective, determining
the type of data to collect, repeated measures and blocking, choosing
the sample and the randomization technique, designing a data collection
form. Applications to biomedical data.

STA6201Analysis of Research Data (Spring)


Credits: 3

Prereq: STA 6200

Introduction to the most commonly used
statistical analyses for evaluating research data, with application to
the biomedical sciences. Emphasis on choosing the appropriate procedure
and evaulauing the results properly, rather than on the computational
aspects of the procedures.

STA 6207Basic Design and Analysis of
Experiments (Fall)


Credits: 3

Prereq: STA 4322

Overview of normal theory inference,
nonparametric, and categorical data methods; basic concepts of
experimental design; analysis of variance; introduction to factorial
and nested experiments.

STA 6208Regression Analysis (Spring)


Credits: 3

Prereq: STA 6207

Simple linear regression; multiple regression;
model selection residual analysis; influence diagnostics;
multicollinearity; ANOVA and regression; generalized linear models;
nonlinear regression.

STA 6209Design and Analysis of Experiments
(Spring)


Credits: 3

Prereq: STA 6208

Tests of assumptions; block designs; control of
twoway heterogeneity; cross over designs; factorial experiments;
fractional factorials; analysis of "messy" data.

Credits: 3

Prereq: STA 6327 or consent of instructor

Theory and application of commonly used
sampling techniques; simple random sample, cluster, ratio, regression,
stratified, multistage, and systematic samples. Special topics include
wildlife surveys, nonsampling error adjustment, categorical data
analysis, and practical survey examples.

STA 6246Theory of Linear Models (Fall)


Credits: 3

Prereq: STA 6208 and STA 6327 and STA 6329

Theory for analysis of linear models in
univariate data; distributions of quadratic forms; full rank linear
models; fixed effect models of less than full rank; balanced random and
mixed models; unbalanced random and mixed models.

Credits: 3

Prereq: STA 6246 and STA 6207 and STA 6208 and
STA6209

First and second order response surface designs
and models. The objectives of a response surface investigation. The
determination of optimum conditions for response surface models. The
integrated mean square error criterion for the choice of a design.
Minimum bias estimation designs. The analysis of multiresponse
experiments. Designs for nonlinear models. Some advanced topics in
unbalanced mixed models.

Credits: 3

Prereq: STA 6209 and STA 6246

Estimation of variance components. Best linear
unbiased predication of random effects. Measures of imbalance. Exact
tests for unbalanced random and mixedeffects models. Generalized
Pvalues.

Credits: 3

Prereq: STA 6327

Double sampling procedures, the sequential
probability ratio tests, sequential tests for composite hypotheses,
sequential estimation and confidence intervals.

STA 6326Introduction to Theoretical
Statistics I (Fall)


Credits: 3

Prereq: MAC 2313

Theory of probability. Probability spaces,
continuous and discrete distributions, functions of random variables,
multivariate distributions, expectation, conditional expectation,
central limit theorem, useful convergence results, sampling
distributions, distributions of order statistics, empirical
distribution function.

STA 6327Introduction to Theoretical
Statistics II (Spring)


Credits: 3

Prereq: 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, decision theory, analysis of
categorical data.

STA 6329Matrix Algebra and Statistical
Computing (Fall)


Credits: 3

Prereq: MAC 3313 and STA STA 6208

Basic theory of determinants, inverses and
generalized inverses, eigenvalues and eigenvectors; applications of
partitioned matrices; diagonalization and decomposition theorems;
applications in least squares.

STA 6466Probability Theory I (Fall)


Credits: 3

Prereq: MAA 5228 or equivalent

Measure and probability spaces; random
variables; distribution functions; abstract Lebesgue and Stieltjes
integration; monotone; dominated, Cauchy, and mean convergence; Fubini
and RadonNikodym theorems; zeroone laws.

STA 6467Probability Theory II (Spring)


Credits: 3

Prereq: STA 6466

Summability of independent random variables,
laws of large numbers, convergence in distribution, characteristic
functions, uniqueness and continuity theorems, the LindebergFeller
central limit theorem, degenerate convergence criterion.

STA 6505Analysis of Categorical Data (See
Schedule of Graduate Major Course Offerings)


Credits: 3

Prereq: STA 6327 and STA 6207 or consent of
instructor.

Varieties of categorical data,
crossclassification tables, tests for independence. Measures of
association. Loglinear models for multidimensional tables. Logit
models and analogies with regression. Specialized methods for ordinal
data.

Credits: 3

Prereq: STA 6327 or consent of instructor.

Inference based on rank statistics one, two
and ksample problems, correlation and regression problems and analysis
of contingency tables. Conditionally distributionfree rank tests.
Pitman asymptotic relative efficiency.

Credits: 3

Prereq: STA 6526 or consent of instructor

Theoretical foundations of nonparametric
statistics: theory of Ustatistics, Noether's theorem and Pitman
asymptotic relative efficiency, estimation and hypothesis testing with
one and two sample models, theory of linear rank statistics,
applications to general linear models analyses.

STA 6662Statistical Methods for Industrial
Practice (See
Schedule of Graduate Major Course Offerings)


Credits: 3

Prereq: statistical theory of distributions,
basic analysis of variance; coreq: theory of statistical estimation and
testing.

Statistical techniques used in modern industry,
including variance components analysis, control charting, estimation of
process characteristics, evolutionary operation, fraction, factorials,
screening experiments.

STA 6706Applied Multivariate Methods for
Behavioral Research


Credits: 3

Prereq: STA 6166 or consent of instructor.

Bivariate relationship: matrix algebra; review
of multiple regression and correlation; part and partial correlation;
canonical correlation; discriminant analysis and classification;
cluster analysis; factor analysis.

Credits: 3

Prereq: STA 6208 and facility in a computer
language.

Techniques for analyzing multivariate data.
Emphasis on MANOVA and tests on the structure of the dispersion matrix.
Topics will include discriminant, factor, profile, and cluster
analyses.

Credits: 4

Prereq: STA 6246 or consent of instructor.

Singular transformations and the generalized
Jacobian. The multivariate normal distribution, Wishart distribution,
and the U distribution. Distribution of the latent roots of one Wishart
matrix in the metric of another. Noncentral counterparts of these
distributionsan introduction to zonal polynomials. Distributions of
variables constrained to lie on a sphere or a simplex. The resultant
and its usage in analysis of directional data.

Credits: 3

Prereq: STA 6327

Discrete time and state Markov process. Ergodic
theory.

Credits: 4

Prereq: STA 6826

Continuous time Markov processes. The Poisson
and allied processes. The Kolmogorov equations. Renewal theory.

Credits: 3

Prereq: STA 4322 or STA 5328 and a basic
computer language.

Linear time series model building, spectral
density estimation, analysis of nonstationary data, SAS package on Box
and Jenkins model building and forecasting. Case studies in recent
literature will be discussed.

Credits: 3

Prereq: STA 6327

Foundations of stationary time series,
distributions of sample autocorrelations, partial autocorrelation,
spectral density, time series regression, and special topics in recent
time series research.

STA 6900Problems in Statistics (Arrange)


Credits: 14; max: 6

Prereq: permission of department

Special problems in research methods, sampling
methods, and experimental designs.

STA 6905Individual Work (Arrange)


Credits: 14; max: 10

Prereq: Permission of department

Special topics designed to meet the needs and
interests of individual students.

STA 6910Supervised Research (Arrange)


Credits: 15; max: 5

Prereq: Premission of department

S/U

Credits: (13; max: 8)

Prereq: permission of graduate adviser.

STA 6937Seminar: Current Topics in
Statistics


Credits: 13; max: 6

Prereq: Permission of department

Discussion of current research topics in
statistics in statistics not covered in regular courses. S/U

STA 6938Seminar


Credits: 1; max: 15

Prereq: Permission of department

Special topics of an advanced nature suitable
for seminar treatment but not given in regular courses. S/U

STA 6940Supervised Teaching (Arrange)


Credits: 15; max: 5

Prereq: Permission of department

S/U

STA 6942Internship (Fall, Spring, Summer)


Credits: 13; max: 3

Prereq: STA 6208 or equivalent and permission
of graduate coordinator

Supervised statistical consulting involving the
planning and/or analysis of research data. Whenever possible, the
student will meet with the researcher. Supervision by a faculty member
or delegated authority. Post internship report is requirecd. S/U

STA 6971Research for Master's Thesis
(Arrange)


Credits: 115

Prereq: Permission of Department

S/U

STA 7249Generalized Linear Models (See
Schedule of Graduate Major Course Offerings)


Credits: 3

Prereq: STA 6207 and STA 6208 and STA 6327

Fitting of generalized linear models,
diagnostics, asymptotic theory, overdispersion, estimating equations,
mixed models, generalized additive models, smoothing.

Credits: 3

Prereq: STA 6467

Review of different models of convergence.
CramerWold device. Multivariate CLT. Asymptotic theory of empirical
distribution and sample quantiles. Bahadur's representation. Asymptotic
theory of sample moments. Delta method and its multiparameter
generalization. Variance stabilizing transformation. Ustatistics:
asymptotic theory and its statistical applications. Hoeffding's
decomposition. Asymptotic theory of maximum likelihood estimation.
Wald's consistency theorem for MLE. Asymptotic normality and
efficiency. Asymptotic theory of GLRTs. Statistical applications:
asymptotic theory or categorical data, linear models, and generalized
linear models.

STA 7346Statistical Inference I (Fall)


Credits: 3

Prereq: STA 6327

Decision rules and risk functions. Sufficiency,
Minimax, and Bayes rules for estimation of location and scale
parameters.

STA 7347Statistical Inference II (Spring)


Credits: 3

Prereq: STA 7346

Bayesian statistical inference. Inference using
large samples. Relative efficiencies of tests and estimates with
special reference to Pitman and Bahadur efficiencies.

STA 7506Advanced Categorical Data Analysis
(See
Schedule of Graduate Major Course Offerings)


Credits: 3

Prereq: STA 6327 and STA 6208 and STA 6505

Models for multinomial responses such as
original data, models for matched pairs and more complex types of
repeated categorical measurement data, and smallsample and
largesample theory for parametric model fitting and recent research in
categorical data analysis.

STA 7979Advanced Research (Arrange)


Credits: 112

Prereq: Permission of Department

Research for doctoral students before admission
to candidacy. Designed for students with a master's degree in the field
of study or for student who have been accepted for a doctoral program.
Not open to students who have been admitted to candidacy. S/U

STA 7980Research for Doctoral Dissertation
(Arrange)


Credits: 115

Prereq: Permission of Department

S/U

MAA 6236Mathematical Analysis for
Statisticians (Fall)


Credits: 3

Prereq: STA 4322

Numerical sequences and series, limits,
continuity, differentiation, integration, series of functions.
Applications to probability and statistics stressed.

**NOTE: A Schedule of Courses is
also kept in the Graduate Catalog kept by the Office of
Research and Graduate Programs