THE UNIVERSITY OF ALABAMA GRADUATE CATALOG
Table of Contents > Manderson Graduate School of Business

7.6.13 STATISTICS (ST)
Head: Professor Charles Sox, Office: 304 Alston Hall
 
ST 509 Statistics for Business Applications. Three hours.
Prerequisite: Admission to the MS program.
A broad introduction to statistical and probabilistic methods useful for managerial decision making. Topics include graphical displays, numerical summaries, basic probability models, confidence intervals, hypothesis testing, and regression analysis.

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 522 Advanced Statistical Data Management. Three hours.
Prerequisite: ST 521 or equivalent.
This course provides students with insight and understanding into the advanced aspects of data management. Emphasis will be placed on computer techniques for the preparing and cleaning of data from scientific research projects as well as for business-oriented projects in order to conduct advanced level analyses. Techniques for detecting, quantifying, and correcting data quality will be covered.

ST 531 Knowledge Discovery and Data Mining I. Three hours.
Prerequisite: ST 550, ST 560 or ST509 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 532 Advanced Data Mining. Three hours.
Prerequisite: ST 531 or equivalent.
A detailed study of data mining techniques including logistic regression, neural networks, decision trees, general classifier theory, and unsupervised learning methods. Mathematical details and computer techniques are examined. The SAS programming language and SAS's Enterprise Miner will be used to accomplish these tasks. Other packages may also be 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, ST 560. 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 450 or ST 550 or ST 560 or ST 509.
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 collinearity. 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. Three hours. (same as MATH 554).
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. Three hours.  (same as MATH 555).
Prerequisite: ST 554.
Theory of order statistics, point estimation, interval estimation, and hypothesis testing.

ST 560 Statistical Methods in Research I. Three hours.
Prerequisite: MATH 121 or 125.
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 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 550 or ST 560 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 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 Nonparametric Statistics. Three hours.
Prerequisite: ST 554 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 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 697 Special Topics. Variable credit.

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.

THE UNIVERSITY OF ALABAMA GRADUATE CATALOG

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