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Professor Edward R. Mansfield, Head
Office: 300 Alston Hall
ST 405 Mathematics for Quantitative Analysis. Three hours.
Prerequisite: MATH 121.
Differential and integral calculus, maxima, curve tracing, sequences and series, and vectors and matrices.
ST 450 Statistical Methods for Applied Research I. Three hours.
Development of fundamental concepts of organizing, exploring, and summarizing data; probability; common probability distributions; sampling and sampling distributions; estimation and hypothesis testing for means, proportions, and variances using parametric and nonparametric procedures; power analysis; goodness of fit; contingency tables. Statistical software packages are used extensively to facilitate valid analysis and interpretation of results. Emphasis is on methods and on selecting proper statistical techniques for analyzing real situations.
ST 451 Statistical Methods for Applied Research II. Three hours.
Prerequisite: One of the following - GES 400, GES 500, BER 540, CHS 425, CHS 525, ST 450, ST 550.
Analysis of variance and design of experiments, including randomization, replication, and blocking; multiple comparisons; correlation; simple and multiple regression techniques including variable selection, detection of outliers, and model diagnostics. Statistical software packages are used extensively to facilitate valid analysis and interpretation of results. Emphasis is on appropriate analysis of data in real situations.
ST 465 Sampling Techniques. Three hours.
Prerequisite: ST 251 or equivalent.
Planning, execution, and evaluation of sample surveys. Simple, random, stratified, and cluster sampling; multistage and systematic sampling; questionnaire design; cost functions; and optimal designs. Teams will plan, perform, and analyze actual sample surveys.
ST 475 Statistical Quality Control. Three hours.
Prerequisite: ST 251 or equivalent.
Statistical methods useful in control and improvement of manufactured products, including statistical process control with variables and attribute control charts, and process improvement with designed experiments. Emphasis is placed on design, implementation, and interpretation of the techniques.
ST 509 (M.B.A.) Statistics for Business Applications. Three hours.
A broad elementary introduction to statistical and probabilistic methods useful for managerial decision making. The course requires three hours of lecture and one hour of laboratory work per week. The laboratory is used to expose the student to computer software applications.
ST 521 Statistical Data Management. Three hours.
Introduction to the management of data using SAS. The collection and management of data from business or scientific research projects are emphasized.
ST 525 Statistics for Business Decisions. Three hours.
Prerequisite: ST 251 or equivalent.
Methods of classical and Bayesian statistics are applied to business decisions.
ST 531 Knowledge Discovery and Data Mining I. Three hours.
Prerequisite: ST 550 or ST 560 or equivalent.
Data mining is the process of selecting, exploring, and modeling large amounts of data to uncover previously unknown patterns of data. Techniques for accomplishing these tasks in a business setting will be discussed.
ST 535 Nonparametric Statistics. Three hours.
Prerequisite: ST 550 or equivalent.
Theory and applications of various nonparametric statistical methods are covered for one-sample, two-sample, and multi-sample problems. Goodness of fit techniques such as Chi-square and the Kolmogorov-Smirnov test are covered along with graphical analysis based on P-P and Q-Q plots. Computer software such as MINITAB, SAS, and STATXACT are used.
ST 550 Statistical Methods for Applied Research I. Three hours.
Development of fundamental concepts of organizing, exploring, and summarizing data; probability; common probability distributions; sampling and sampling distributions; estimation and hypothesis testing for means, proportions, and variances using parametric and nonparametric procedures; power analysis; goodness of fit; contingency tables. Statistical software packages are used extensively to facilitate valid analysis and interpretation of results. Emphasis is on methods and on selecting proper statistical techniques for analyzing real situations.
ST 551 Statistical Methods for Applied Research II. Three hours.
Prerequisite: One of the following - GES 400, GES 500, BER 540, CHS 425, CHS 525, ST 450, ST 550.
Analysis of variance and design of experiments, including randomization, replication, and blocking; multiple comparisons; correlation; simple and multiple regression techniques including variable selection, detection of outliers, and model diagnostics. Statistical software packages are used extensively to facilitate valid analysis and interpretation of results. Emphasis is on appropriate analysis of data in real situations.
ST 552 Applied Regression Analysis. Three hours.
Prerequisite: ST 451, ST 551, or ST 561.
Modeling issues for multiple linear regression are discussed in the context of data analysis. These include the use of residual plots, transformations, hypothesis tests, outlier diagnostics, analysis of covariance, variable selection techniques, weighted least squares and colinearity. The uses of multiple logistic regression are similarly discussed for dealing with binary-valued dependent variables.
ST 553 Applied Multivariate Analysis. Three hours.
Prerequisite: ST 451, ST 551, or ST 561.
Methods and business applications of multivariate analysis, discriminant analysis, canonical correlation, factor analysis, cluster analysis, and principal components.
ST 554 Mathematical Statistics I (same as MATH 554). Three hours.
Prerequisite: MATH 227.
Distributions of random variables, moments of random variables, probability distributions, joint distributions, and change of variable techniques.
ST 555 Mathematical Statistics II (same as MATH 555). Three hours.
Prerequisite: ST 554.
Theory of order statistics, asymptotic distributions, point estimation, interval estimating, and hypothesis testing.
ST 560 Statistical Methods in Research I. Three hours.
Prerequisite: MATH 126.
Statistical methods for summarizing data; probability; common probability distributions; sampling and sampling distributions; estimation and hypothesis testing for means, proportions, and variances using parametric and nonparametric procedures; power analysis; goodness of fit; contingency tables; and simple regression and one-way analysis of variance.
ST 561 Applied Design of Experiments. Three hours.
Prerequisite: One of the following - GES 400, GES 500, BER 540, CHS 425, CHS 525, ST 450, ST 550, ST 560.
An introduction to the design and analysis of experiments. Topics include factorial, fractional factorial, block, incomplete block, and nested designs. Other methods discussed include Taguchi Methods, response surface methods, and analysis of covariance.
ST 565 Sampling Techniques. Three hours.
Prerequisite: ST 251 or equivalent.
Planning, execution, and evaluation of sample surveys. Simple, random, stratified, and cluster sampling; multistage and systematic sampling; questionnaire design; cost functions; and optimal designs. Teams will plan, perform, and analyze actual sample surveys.
ST 570 Time Series Analysis. Three hours.
Prerequisite: ST 551, EC 671, or permission of the instructor.
Modeling of both stationary and non-stationary time series. Autoregressive (AR) processes and moving average (MATH) processes, as well as mixed (ARMA) processes, are discussed, along with model identification and estimation and forecasting procedures. Computer software is used.
ST 575 Statistical Quality Control. Three hours.
Prerequisite: ST 251 or equivalent.
Statistical methods useful in control and improvement of manufactured products, including statistical process control with variables and attribute control charts, and process improvement with designed experiments. Emphasis is placed on design, implementation, and interpretation of the techniques.
ST 580 Analysis of Categorical-Level Data. Three hours.
Prerequisite: ST 451 or ST 560.
Logit and probit models, including dichotomous and multichotomous response functions; discrete choice models; log-linear models for multi-way contingency tables; procedures for analyzing ordinal-level data.
ST 591 Independent Study in Statistics. Three hours.
ST 592 Internship in Statistics. Three hours.
ST 597 Special Topics in Statistics. Variable credit.
ST 598 Research in Statistics. Variable credit.
ST 599 Thesis Research in Statistics. Variable credit.
ST 603 Advanced Inference. Three hours.
Prerequisite: ST 555 or equivalent.
A continuation of ST 555, with emphasis on the general theory of estimation and hypothesis testing and large sample distribution theory.
ST 610 Linear Models. Three hours.
Prerequisite: ST 555 or equivalent.
Gauss-Markov Theorem, solution of linear systems of less than full rank, generalized inverse of matrices, distributions of quadratic forms, and theory for estimation and inference for the general linear model.
ST 611 Design and Analysis of Experiments. Three hours.
Prerequisite: ST 610.
General theory for analysis of block designs, balanced and partially balanced incomplete block designs. Latin/Graeco-Latin/Youden Squares, analysis of factorial treatments in arbitrary block designs to include fractional factorials, confounding, and aliasing.
ST 615 Theory of Regression. Three hours.
Prerequisite: ST 610.
Theory of the general linear regression models and inference procedures, variable selection procedures, and alternate estimation methods including principal components regression, robust regression methods, ridge regression, and nonlinear regression.
ST 635 Multivariate Analysis. Three hours.
Prerequisite: ST 610 or equivalent.
Multivariate normal distributions, inference, multiple and partial correlation, classification, multivariate analysis of variance, principle components, factor analysis, and canonical analysis.
ST 640 Statistical Computing. Three hours.
Prerequisites: ST 552 or its equivalent; MATH 237 or its equivalent; and experience with a computer programming language such as FORTRAN, C, Pascal, or Basic; or permission of the instructor.
Topics include a survey of current statistical software, numerical methods for statistical computations, nonlinear optimization, statistical simulation, and recent advances in computer-intensive statistical methods.
ST 675 Advanced Statistical Quality Control. Three hours.
Prerequisite: ST 555, ST 575, or equivalent.
Theoretical approaches to statistical process control procedures and the design of experiments for quality improvement.
ST 698 Research in Statistics. Three hours.
Open only to graduate students nearing completion of coursework. Independent study and investigation of specific problems for advanced students of statistics.
ST 699 Dissertation Research. Variable credit. Three-hour minimum.
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