Graduate Bulletin-School of Business and Management

Introduction to certain statistical problems associated with pharmaceutical drug development. Topics include the bioequivalence problems, population PK/PD modeling, and analysis of combination drug trials. Research articles of current interest will be discussed.

585. Exploratory Data Analysis I. (3 s.h.)

Prerequisite: Stat. 502 or 504 or permission of instructor.

Acquaints the student with applications of statistical theory. Techniques and solutions for a broad spectrum of real-world problems. Statistical computing emphasized.

598-599. Independent Study. (1-6 s.h.)

Prerequisite: approval of the department.

Special study in a particular aspect of statistics under the direct supervision of an appropriate graduate faculty member. No more than six semester hours of independent study may be counted toward degree requirements.

601. Advanced Statistical Inference I. (3 s.h.)

Prerequisite: Stat. 502.

Random variables, inequalities, convergence types, Central Limit Theorem, integration and expectation, conditional probability and expectation, UMVU estimator, Bayes and Minimax estimators.

602. Advanced Statistical Inference II. (3 s.h.)

Prerequisite: Stat. 601.

Hypothesis testing and confidence sets, Neyman-Pearson Lemma, similar and unbiased tests, likelihood ratio tests.

618. Time Series Analysis II. (3 s.h.)

Prerequisite: Stat. 518 or permission of instructor.

Advanced topics on modern time series analysis from the time domain and/or frequency domain perspective. Emphasis will be placed on the analysis of multiple time series.

621. Linear Models II. (3 s.h.)

Prerequisite: Stat. 521 or permission of instructor.

Continuation of Stat. 521, principally devoted to analysis of mixed models and inference concerning variance components. Topics covered include calculation of expected mean squares, estimation by Henderson's Methods, ML, REML, MINQUE, MIVQUE. Dispersion Mean Model. Computational algorithms and software.

622. Design of Experiments II. (3 s.h.)

Prerequisite: Stat. 522 or permission of instructor.

Covers symmetric and asymmetrical factorial experiments, fractional replication, split plot design, balanced and partially balanced incomplete block designs without and with recovery of interblock information and lattice designs.

633. Multivariate Analysis II. (3 s.h.)

Prerequisites: Stat. 502 and 533 or permission of instructor.

A study of specialized topics in multivariate analysis.

662. Biometric Methods. (3 s.h.)

Prerequisite: Stat. 502 or permission of instructor.

Presents the theory of biometry and explores its many applications. Topics are taken from clinical trials, bioassay and survival analysis. Topics discussed include the importance of randomization, parallel assays, censored data, proportional hazard models, and rank tests.

701-702. Seminar in New Topics in Statistics. (3 s.h. each semester)

Prerequisite: permission of instructor.

Special topics in Statistics.

799. Directed Study in Statistics. (variable credit)

Prerequisite: departmental permission.

Preparation for preliminary examinations.

800. Quantitative Business Methods. (3 s.h.)

Introduces descriptive statistical tools which are commonly used in business and decision making. Basic probability concepts are covered and are employed using statistical inference methods. Estimation, testing of hypotheses and applications. Statistical package "Minitab" will be used as a tool for not only computations but also for understanding statistical concepts. The course will be rigorous in statistical concepts.

802. Managerial Statistics. (3 s.h.)

Study advanced statistical techniques for managerial decision making, including the theory and application of regression, time series and forecasting, categorical data analysis, and quality improvement techniques. Statistical packages, business data sets, and case studies are used.

896-899. Directed Study in Statistics. (variable credit)

Prerequisite: departmental permission.

999. Dissertation Research. (1-12 s.h.)

Prerequisite: departmental approval.

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