Graduate Statistics (STAT) Courses

Graduate level courses in statistics are designed to constitute a minor, supplementing
graduate students' courses of study in their major areas.  No degree is offered in
Statistics.

5331.  Statistical Computing.  3(3-0)
Provides the computer tools for modern research analysis.  Introduction to use of
computer and statistical software.  Includes applications of SAS to data entry,
experimental design, regression, surveys.
Prerequisite:  One statistics course or equivalent.  Laboratory Fee  $5.00

5332. Big Data and Computing. 3(3-0)
Introduction to use of SAS (and R)/PC statistical software, including data
entry, data summaries, descriptive statistics, and interpretation of SAS
(and R) output for some standard statistical procedures.
Prerequisite STAT 5344 or equivalent.

5343.  Applied Regression Analysis.  3(3-0)
Multiple regression analysis, selecting the "best" regression equation, general
model building, introductory linear models.
Prerequisite:  an advanced statistics course.  Laboratory Fee, $5.00

5344. Predictive Analytics. 3(3-0)
Correlation, simple linear and multiple regression, one and two way ANOVA,
various multiple comparison procedures, randomized block designs, applications,
use of statistical software.
Prerequisite:  STAT 4301 or STAT 4303 or equivalent.

5345.  Analysis of Research Data.  3(3-0)
Basic concepts and techniques for research, including completely randomized
design, factorial, randomized complete block, split-plot, Latin square and analysis of
variance.
Prerequisite:  One statistics course or equivalent.  Laboratory Fee, $5.00

5346. Design of Experiments 3(3-0)
Hypothesis testing, principles of design of an experiment, t-test, completely
randomized design, randomized block design, multiple comparison techniques,
factorial designs, random effect models, fixed effect models, BIBD, nested
designs, analysis of covariance and split plot designs.
Prerequisites:  STAT 4301 or STAT 4303 or equivalent.

5350. Probability for Analytics. 3(3-0)
Mathematical treatment of probability distributions, probability concepts
and laws; sample spaces, combinations and permutations, Bayes'
theorem, discrete/continuous random variables, expected value, distribution
of functions of random variable, two-dimensional variables, central limit
theorems; t, F, and chi-square distributions.
Prerequisite:  STAT 4301 or STAT 4303 or equivalent.

5351. Inferential Analytics. 3(3-0)
Theory of estimation and hypothesis testing, maximum likelihood,
method of moments, likelihood ratio tests, consistency, bias, efficiency
and sufficiency.
Prerequisite:  STAT 5350 or equivalent.

5361. Multivariate Statistics. 3(3-0)
An applied approach to multivariate data analysis and linear statistical 
models in research.  Prerequisite:  MATH 4341 and STAT 5344 or
equivalents.

5362. Nonparametric Statistics. 3(3-0)
Estimation and hypothesis testing, models for categorical data,
classical rank-based nonparametric methods, permutation tests,
bootstraps methods, and curve smoothing
Prerequisite:  STAT 4301 or STAT 4303  or equivalent.

5370. Survey Sampling Analytics. 3(3-0)
Survey sampling from initial planning phases through collection and
storage of the data; simple random sampling, stratified random
sampling, auxiliary information estimators, chi-square contingency
table analysis for two and three way tables, handling of small expected
frequencies, matched pairs, measures of association; use of statistical
software on big survey data.
Prerequisite:  STAT 4301 or STAT 4303 or equivalent.

5372. Model Assisted Survey Methods. 3(3-0)
Probability proportional to size sampling, auxiliary information
Horvitz and Thompson estimator, calibration of design weights,
model assisted calibration techniques,  GREG and linear regression
estimator, imputation of missing data, bootstrap and jackknifing.
Prerequisite:  STAT 5340 or equivalent

5374. Survey Models for Social Science. 3(3-0)
Sensitive data and privacy issues in survey sampling.  Randomized
response models and variations.  Estimation of prevalence
of two or more sensitive characteristics.  Use of Cramer-Rao
lower bound of variance.  Measures of protection of respondents.
Models using complex designs.
Prerequisite:  STAT 4301, 4303 or PSYC/SOCI 3381 or equivalent.

5375. Operataions Research. 3(3-0)
Geometric linear programming.  the Simplex method, duality theory,
sensitivity analysis, project planning and integer programming.
Optional topics include, but are not limited to:  the transportation
problem, the upper bounding technique, the dual Simplex methoid,
parametric linear programming, queuing theory, decision analysis,
and simulation.
Prerequisite: Any introductory course in Linear Algebra.

5380. Survival Analysis. 3(3-0)
Statistical analysis of time-to-event or survival data.  Basic
Terminology and both parametric and non-parametric techniques.
Continuous and discrete time regression models and partial
likelihood estimation.  Includes competing risk models,
unobserved heterogeneity, and multaivariate survival models
including event history.
Prerequisite: STAT 5305 and STAT 5351 or equivalents.

5390.  Advanced Topics in Statistics.  3(3-0)
Different areas of advanced statistics will be covered at separate offerings of this
course.  Topics include sampling techniques, multivariate analysis, quality
control techniques.  May be repeated once.
Prerequisite:  6 semester hours of advanced statistics or the equivalent. 
Laboratory Fee, $5.00

This page was last updated on: November 16, 2017