John D. Elwin, Ph.D., Professor of Mathematical and Computer Sciences, Chair of Department
Amanda L. Golbeck, Ph.D., Professor of Mathematical and Computer Sciences
Kung-Jong Lui, Ph.D., Professor of Mathematical and Computer Sciences (Statistics Coordinator and M.S. Biostatistics Graduate Adviser)
Joseph M. Moser, Ph.D., Professor of Mathematical and Computer Sciences
Chong Jin Park, Ph.D., Professor of Mathematical and Computer Sciences (M.S. Statistics Graduate Adviser)
Colleen Kelly, Ph.D., Associate Professor of Mathematical and Computer Sciences
David W. Macky, Ph.D., Associate Professor of Mathematical and Computer Sciences
Duane L. Steffey, Ph.D., Associate Professor of Mathematical and Computer Sciences
Graduate teaching associateships in statistics and biostatistics are available and are awarded on a competitive basis by the Department of Mathematical and Computer Sciences. Application forms and additional information may be secured from the office of the Department of Mathematical and Computer Sciences.
The Department of Mathematical and Computer Sciences offers graduate study leading to the Master of Science degree in statistics. Students may pursue either the general degree or a concentration in biostatistics that emphasizes statistical methods and applications in the biological, health, and medical sciences.
Statisticians and biostatisticians are engaged in the acquisition and use of knowledge through the collection, analysis, and interpretation of data. Today, almost all disciplines - from economics to engineering, from social science to medicine - employ statistical methods. Such methods are essential in studying relationships, predicting results, and making informed decisions in many different contexts. This diversity of application of this field has stimulated the current demand for well-trained statisticians and biostatisticians at all degree levels.
The Master of Science degree provides advanced training, with emphasis on statistical methodology, and prepares students for careers in industry and government as applied statisticians or biostatisticians, or for entry into a doctoral program in statistics or biostatistics.
As part of the degree requirements, graduate students conduct theses or research projects under the guidance of faculty with active research interests in most general areas of probability, statistics, and biostatistics. These research areas include -biostatistical methods, survival analysis, mathematical demography, data analysis, inference, stochastic processes, time series, Bayesian statistics, categorical data analysis, statistical computing, nonparametric statistics, sample surveys, multivariate analysis, linear models, experimental design, and clinical trials.
All students must satisfy the general requirements for admission to the University with classified graduate standing, as described in Part Two of this bulletin.
All students must satisfy the general requirements for advancement to candidacy as described in Part Two of this bulletin.
In addition to meeting the requirements for classified graduate standing and the basic requirements for the master's degree as described in Part Two of this bulletin, the students must meet the following program requirements:
The student should have completed before entering the program the following undergraduate coursework: three semesters of calculus; and one semester each of linear algebra and probability theory. The student should also have working knowledge of a programming language before entering the program. Students lacking some of the above undergraduate coursework may be admitted conditionally and may make up this coursework during the first year of the program (these courses will not count toward the degree course requirements).
The student must complete a minimum of 30 units of coursework as described below. Upon entry to the program, the student will be assigned to a graduate adviser in statistics. Thereafter, the adviser will meet with the student each semester and discuss his or her academic program. A program of study must be approved by the graduate adviser in statistics.
1. Complete Statistics 670A, 670B, and 552 with no grade less than B in each course. These are core statistics courses.
2. Complete nine units of courses in statistics and biostatistics, selected from the following with the approval of the graduate adviser in statistics: Statistics 553, 671, 672, 674, 675, 676, 677, 678, 679, 680A, 680B.
3. Complete three additional units of 600- and 700-numbered courses offered by the Department of Mathematical and Computer Sciences, except that Mathematics 600, 601, 602, and Statistics 799A may not be used to fulfill these units required.
4. Complete three additional units of graduate level or approved 500-level courses offered by the Department of Mathematical and Computer Sciences, not including Statistics 799A.
5. Complete three units of approved electives.
6. The thesis option (Plan A) requires the approval of the graduate adviser and the statistics division faculty member who will chair the committee. Students in Plan A must include Statistics 799A in the 30-unit program and are required to pass a final oral examination on the thesis, open to the public.
7. Students in the non-thesis option (Plan B) are required to complete three units of Statistics 797, prepare a written project report, and pass an examination. Policy and procedures for the Plan B report and examination are documented and available from the office of the Department of Mathematical and Computer Sciences.
In addition to meeting the requirements for classified graduate standing and the basic requirements for the master's degree as described in Part Two of this bulletin, the student must meet the following program requirements:
The student should have completed before entering the program the following undergraduate coursework: three semesters of calculus and one semester each of linear algebra and probability theory. The student should also have working knowledge of a programming language before entering the program. Students lacking some of the above undergraduate coursework may be admitted conditionally and may make up this coursework during the first year of the program (these courses will not count toward the degree course requirements).
The student must complete a minimum of 30 units of coursework as described below. Upon entry to the program, the student will be assigned to a graduate adviser in biostatistics. Thereafter, the adviser will meet with the student each semester and discuss his or her academic program. A program of study must be approved by the graduate adviser in biostatistics.
1. Complete Statistics 670A, 670B, and 552 with no grade less than B in each course. These are core statistics courses.
2. Complete Statistics 680A and 680B with no grade less than B in each course. These are biostatistics concentration courses.
3. Complete at least six units of courses in biostatistics and statistics, selected from the following with the approval of the graduate adviser in biostatistics: Statistics 553, 554A, 554B, 555, 596, 671, 672, 674, 675, 676, 677, 678, 679, 696, 720, and 798.
4. Complete at least six units of 500-level or graduate courses from a science of application of biostatistics (e.g., bioscience, health science, or medical science), selected with the approval of the graduate adviser in biostatistics. If the student has an undergraduate degree in an area of application of biostatistics, 500-level or graduate mathematical sciences courses may be substituted with the approval of the graduate adviser in biostatistics.
5. With the approval of the graduate adviser and the faculty member who will chair the thesis committee, the student may choose Plan A and complete three units of Statistics 799A. The chair of the thesis committee must be a faculty member from the division of statistics in the Department of Mathematical and Computer Sciences. One of the other two members of the thesis committee must be a faculty member from a science of application of biostatistics (i.e., bioscience, health science, or medical science). The student must pass an oral defense of the thesis, open to the public.
6. In other cases, Plan B will be followed. Students who choose Plan B are required to complete three units of Statistics 797, prepare a written project report, and pass an examination. Policy and procedures for the Plan B report and examination are documented and available from the office of the Department of Mathematical and Computer Sciences.
(Note: Statistics 550, 551A, or 551B are not acceptable on the Master of Science degree in Statistics.)
(Note: Proof of completion of prerequisites required for all upper division courses: Copy of transcript.)
550. Probability (3) I, II, S
Prerequisite: Mathematics 151.
Computation of probability by enumeration of cases, discrete and continuous random variables, density functions, moments, limit theorems, selected distributions. Markov chains, random walks, selected topics. (Formerly numbered Mathematics 550.)
551A. Mathematical Statistics (3) I, II
Prerequisite: Mathematics 252.
Probability models in the theory of statistics, sampling distributions with applications in statistical inference. (Formerly numbered Mathematics 551A.)
551B. Mathematical Statistics (3) II
Prerequisite: Statistics 551A.
Point and interval estimation and hypothesis testing in statistical models with applications to problems in various fields. (Formerly numbered Mathematics 551B.)
552. Sample Surveys (3) I
Prerequisite: Statistics 550 or 551A.
Methods for design and analysis of sample surveys with applications to social and biological sciences. Simple random sampling, stratification and clustering, ratio and regression estimators, subsampling, selected topics in survey methodology. (Formerly numbered Mathematics 673.)
553. Stochastic Processes (3)
Prerequisite: Statistics 550 or 551A.
Introduction to stochastic processes with selected applications. (Formerly numbered Mathematics 553.)
554A. Computer Oriented Statistical Analysis (3) I
Prerequisite: Statistics 350A.
Using statistical computer packages such as BMDP and SAS to analyze problems in univariate ANOVA, multiple regression, contingency tables, nonparametric methods and discriminant analysis. (Formerly numbered Mathematics 554A.)
554B. Advanced Computer Oriented Statistical Analysis (3) II
Prerequisite: Statistics 554A.
Analyze problems in multivariate ANOVA, factor analysis, repeated measures, logistic regression, loglinear models, cluster analysis. Using statistical computer packages. (Formerly numbered Mathematics 554B.)
555. Multivariate Statistical Methods in Biology (3)
(Same course as Biology 597B.)
Two lectures and three hours of laboratory.
Prerequisite: Statistics 350A.
Application of multivariate statistical methods in the biological sciences. (Formerly numbered Mathematics 555.)
596. Advanced Topics in Statistics (1-4) I, II
Prerequisite: Consent of instructor.
Selected topics in statistics. May be repeated with the approval of the instructor. See Class Schedule for specific content. Limit of nine units of any combination of 296, 496, 596 courses applicable to a bachelor's degree. Maximum credit of six units of 596 applicable to a bachelor's degree. Maximum combined credit of six units of 596 and 696 applicable to a 30-unit master's degree.
670A-670B. Advanced Mathematical Statistics (3-3)
Prerequisite: Statistics 550 or 551A. Statistics 670A is prerequisite
to 670B.
Distribution of random variables, characteristic functions, limiting distributions, sampling distributions, hypothesis testing and estimation, optimality considerations, applications of the linear hypothesis, invariance and unbiasedness to analysis of variance and regression problems, sequential techniques, decision theory. (Formerly numbered Mathematics 670A-670B.)
671. Statistical Computing (3)
Prerequisite: Statistics 551B or 670B.
Machine computation in the development, application, and evaluation of advanced statistical techniques. Floating point arithmetic and algorithm stability; numerical methods for parameter estimation (including maximum likelihood) and multivariate probability integration; Monte Carlo simulation and other computer-intensive statistical techniques. (Formerly numbered Mathematics 671.)
672. Nonparametric Statistics (3)
Prerequisite: Statistics 551B or 670B.
Theory and application of commonly used distribution-free test statistics, including sign and Wilcoxon tests, and corresponding nonparametric point and interval estimators. Kruskal-Wallis and Friedman tests for analysis of variance, nonparametric regression methods, and other selected topics. (Formerly numbered Mathematics 672.)
674. Multivariate Analysis (3)
Prerequisites: Mathematics 524 and Statistics 551B or 670B.
Multivariate normal distributions, multivariate analysis of variance, factor analysis, canonical correlation. (Formerly numbered Mathematics 674.)
675. Linear Statistical Models (3)
Prerequisites: Statistics 551B or 670B and Mathematics 524.
Multivariate normal distribution; distribution of quadratic forms; linear and curvilinear models; general linear hypothesis of full rank, regression models. (Formerly numbered Mathematics 675.)
676. Bayesian Statistics (3)
Prerequisite: Statistics 551B or 670B.
Bayes' theorem; conjugate priors; likelihood principle; posterior probability intervals; Bayes factors; prior elicitation; reference priors; computational techniques; hierarchical models; empirical and approximate Bayesian inference; posterior sensitivity analysis; decision theory.
677. Design of Experiments (3)
Prerequisite: Statistics 550 or 551A.
Methods for design and analysis of experiments with applications to industry, agriculture, and medicine. Concepts of randomization, blocking, and replication. Incomplete block designs, fractional factorial experiments, response surface methods, selected topics. (Formerly numbered Mathematics 677.)
678. Survival Analysis (3)
Prerequisites: Statistics 551B or 670B.
Survival distributions; inference in parametric survival models; life tables; proportional hazards model; time-dependent covariates; accelerated time model and inference based on ranks; multivariate time data and competing risks. (Formerly numbered Mathematics 678.)
679. Analysis of Discrete Data (3)
Prerequisite: Statistics 551B or 670B.
Discrete sampling models; goodness-of-fit testing; methods for binary data with covariates, including logistic regression and probit analysis; loglinear modeling of multidimensional contingency tables; ordered categories; incomplete tables; Bayesian methods; hierarchical models. (Formerly numbered Mathematics 679.)
680A-680B. Advanced Biostatistical Methods (3-3)
Prerequisites: Statistics 550 or 551A. Statistics 680A is prerequisite
to 680B.
Design, conduct, and analysis of experimental and observational studies. Cohort studies. Multifactor screening. Survival studies. Case-control studies. Biological assays. Selected current topics. (Formerly numbered Mathematics 680A-680B.)
696. Selected Topics in Statistics (3)
Prerequisite: Graduate Standing.
Intensive study in specific areas of statistics. May be repeated with new content. See Class Schedule for specific content. Maximum combined credit of six units of 596 and 696 applicable to a 30-unit master's degree.
720. Seminar (1-3)
Prerequisite: Consent of instructor.
An intensive study in advanced statistics. May be repeated with new content. See Class Schedule for specific content. Maximum credit six units applicable to a master's degree.
797. Research (1-3) Cr/NC/SP
Prerequisite: Six units of graduate level statistics.
Research in one of the fields of statistics. Maximum credit six units applicable to a master's degree.
798. Special Study (1-3) Cr/NC/SP
Prerequisite: Consent of staff; to be arranged with department
chair and instructor.
Individual study. Maximum credit six units applicable to a master's degree.
799A. Thesis or Project (3) Cr/NC/SP
Prerequisites: An officially appointed thesis committee and
advancement to candidacy.
Preparation of a project or thesis for the master's degree.
799B. Thesis Extension (0) Cr/NC
Prerequisite: Prior registration in Thesis 799A with an assigned
grade symbol of SP.
Registration required in any semester or term following assignment of SP in Course 799A in which the student expects to use the facilities and resources of the university; also student must be registered in the course when the completed thesis is granted final approval.
| 
Top of Page
