Statistics
The faculty has approval to offer the following courses in the academic years 19992000 and 20002001; however, not all courses are taught each semester or summer session. Students should consult the Course Schedule to determine which courses and topics will be offered during a particular semester or summer session. The Course Schedule may also reflect changes that have been made to the courses listed here since this catalog was published.
Unless otherwise stated below, each course meets for three lecture hours a week for one semester.
Mathematics: M
384C. Mathematical Statistics.
Same as Computational and Applied Mathematics 384R. General theory of mathematical statistics. Hypothesis testing, estimation, decision theory. Only one of the following may be counted: Computational and Applied Mathematics 684DA, Mathematics 384C, 684DA. Mathematics 384C and 684CA may both be counted; Mathematics 384C and 684CB may both be counted. Prerequisite: Graduate standing and consent of instructor.
384D. Mathematical Statistics.
Same as Computational and Applied Mathematics 384S. Continuation of Mathematics 384C. Only one of the following may be counted: Computational and Applied Mathematics 684DB, Mathematics 384D, 684DB. Prerequisite: Graduate standing, consent of instructor, and Computational and Applied Mathematics 384R (or 684DA) or Mathematics 384C (or 684DA).
384E. Analysis of Variance and Design of Experiments.
Analysis of variance, including the oneway layout and multifactor experiments; mixed, fixed, and random models; crossed and nested classifications. Mathematics 384E and 684EA may not both be counted. Mathematics 384E and 684EB may both be counted. Prerequisite: Graduate standing and consent of instructor.
384F. Analysis of Variance and Design of Experiments.
Experiments with factors at two or three levels, confounding, fractional factorials, response surface methodology. Mathematics 684EB and 384F (Analysis of Variance and Design of Experiments) may not both be counted. Mathematics 384F (Analysis of Variance and Design of Experiments) and 384F (Regression Analysis) may both be counted. Prerequisite: Graduate standing, consent of instructor, and Mathematics 384E (or 684EA).
384G. Regression Analysis.
Fitting linear models to data by the method of least squares, choosing best subsets of predictors, and related materials. Mathematics 384F (Regression Analysis) and 384G (Regression Analysis) may not both be counted. Mathematics 384G (Multivariate Statistical Analysis) and 384G (Regression Analysis) may both be counted. Prerequisite: Graduate standing and consent of instructor.
384H. Multivariate Statistical Analysis.
Introduction to the general multivariate linear model; a selection of techniques, such as principle component, factor, and discriminant analysis. Mathematics 384G (Multivariate Statistical Analysis) and 384H may not both be counted. Prerequisite: Graduate standing and consent of instructor.
385C. Theory of Probability.
Same as Computational and Applied Mathematics 384K. Only one of the following may be counted: Computational and Applied Mathematics 684CA, Mathematics 684CA, 385C. Mathematics 385C and 685CA may both be counted; Mathematics 385C and 685CB may both be counted. Prerequisite: Graduate standing and consent of instructor.
385D. Theory of Probability.
Same as Computational and Applied Mathematics 384L. Continuation of Mathematics 385C. Only one of the following may be counted: Computational and Applied Mathematics 684CB, Mathematics 684CB, 385D. Prerequisite: Graduate standing, consent of instructor, and Computatational and Applied Mathematics 384K (or 684CA) or Mathematics 385C (or 684CA).
394C. Topics in Probability and Statistics.
Same as Computational and Applied Mathematics 394C. Recent topics have included nonparametric statistics, advanced probability. May be repeated for credit when the topics vary. Some topics are offered on the credit/no credit basis only; these are identified in the Course Schedule. Prerequisite: Graduate standing and consent of instructor.
Mathematical Statistics: MST
384J. Frequency Data.
Analysis of data from discrete probability models. Topics include logit and probit regression models and the analysis of complex contingency tables. Prerequisite: Graduate standing, and Mathematics 378K or the equivalent or consent of instructor.
384L. Applied Statistics.
Data analysis and statistical inference. Topics include contingency tables, logistic regression, and generalized linear models. Prerequisite: Graduate standing, and Mathematics 378K or the equivalent or consent of instructor.
384P. Quality Assurance.
Shewhart and cumulative sum control charts, acceptance sampling, offline quality control; Taguchi methods. Prerequisite: Graduate standing, and Mathematics 378K or the equivalent or consent of instructor.
398R. Master's Report.
Preparation of a report to fulfill the requirement for the master's degree under the report option. The equivalent of three lecture hours a week for one semester. Offered on the lettergrade basis only. Prerequisite: Graduate standing in statistics and consent of the supervising professor and the graduate adviser.
