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SWSC 298-I. Individual Internship (1-12) Internship, 3-36 hours. Prerequisite(s): graduate standing in Soil and Water Sciences. Individual study or apprenticeship with an appropriate professional individual or organization and an academic advisor to gain professional experience and knowledge on a topic related to soil or water quality. Graded Satisfactory (S) or No Credit (NC). Course is repeatable but only 6 units may be used toward the 36 units required for the M.S. degree.

Admission All applicants must fulfill the standard admission requirements as established by the Graduate Division. Additionally, applicants must submit a Statement of Purpose to indicate a serious interest in Southeast Asian Studies (or a specific country or area in this region) as well as a writing sample (such as a past term paper or course essay) to demonstrate basic skills of scholarship.

SWSC 299. Research for Thesis or Dissertation (1-12) conference and research, variable time. Prerequisite(s): consent of a staff member. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

Foreign Language Students must acquire (or increase) a distinct level of proficiency in at least one language relevant to Southeast Asian Studies prior to beginning research for the thesis and no later than the fifth quarter in the program. The required proficiency can be demonstrated by way of an exam or by completing one year of course work with a “B” or better.

Professional Course SWSC 302. Teaching Practicum (1-4) F, W, S Practicum, 4-12 hours. Prerequisite(s): graduate standing. Supervised teaching in Soil and Water Sciences or Environmental Sciences courses. Required for all teaching assistants in Soil and Water Sciences. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

Southeast Asian Studies Graduate Program

International students from Southeast Asia may use their native language to fulfill this requirement. Course Work All students are required to pass the Proseminar in Southeast Asian Studies (SEAS 200) with a “B” or better. Additionally, students must pass (with a “B” or better) four of the following six seminar courses: • SEAS 201 Southeast Asian performance • SEAS 202 Southeast Asian religions

• SEAS 205 Literatures of Southeast Asia • SEAS 206 Media in Southeast Asia

René T.A. Lysloff, Ph.D., Director Program Office, 2402 Humanities and Social Sciences (951) 827-5007; seatrip.ucr.edu Committee in Charge Hendrik M.J. Maier, Ph.D. (Comparative Literature and Foreign Languages) Mariam Beevi Lam, Ph.D. (Comparative Literature and Foreign Languages) Sally A. Ness, Ph.D. (Anthropology) Deborah A. Wong, Ph.D. (Music)

Graduate Program The Master's Program in Southeast Asian Studies is an interdepartmental program centered on the study of the arts and cultures of Southeast Asia and its diasporas. To understand Southeast Asia as a region, students need to make sense of and engage with its diverse expressive forms of culture (including visual arts, literature, and performance) which are crucial in building and maintaining individual as well as group identity both within and across national or ethnic boundaries. This program is designed for students with a strong interest in Southeast Asia, including those already admitted or enrolled in another graduate program. Students can be concurrently enrolled in both the Southeast Asian Studies M.A. program and another graduate degree program.

Plan II (Comprehensive Exam) Students concurrently enrolled in another degree program requiring an M.A. thesis may (with the approval of the Southeast Asian Studies faculty) be awarded the M.A. degree by passing a comprehensive examination. University Requirements All master's students must be enrolled for at least three quarters to fulfill the University residency requirement and must hold at least a 3.00 GPA in all upper division and graduate level course work related to the degree. A minimum of 48 units must be completed of which 36 must be graduate level (200 level) or approved upper division undergraduate (100 level) and apply only to the M.A. in Southeast Asian Studies. Normative Time to Degree Two years

Graduate Courses Please see Comparative Literature and Foreign Languages for graduate course listings.

• SEAS 203 Southeast Asian cultures • SEAS 204 History of Southeast Asia

Subject abbreviation: SEAS College of Humanities, Arts, and Social Sciences

of thesis study under the supervision of a Southeast Asian Studies faculty. Before filing the thesis with the Graduate Division students must pass a formal oral examination.

In addition, students can select four other graduate seminars or approved upper division undergraduate courses in accordance with their main field of interest and after approval by the Graduate Advisor and the student's Thesis Committee. A total of 48 units of coursework, including thesis, are required for the degree in Southeast Asian Studies. Students concurrently enrolled in another graduate program may, when appropriate, include units earned in that program toward the 48 units of the M.A. in Southeast Asian Studies. However, there must be at least 36 units uniquely applied to the Southeast Asian Studies degree. Plan I (Thesis) Students enrolled in the Southeast Asian Studies Graduate Program (for the terminal M.A.) must submit an essay (thesis) of 30-40 pages reflecting original research, written under the supervision of a member of the program who also functions as the chair of their Thesis Committee. At the beginning of the second year students should write a research proposal outlining their research project. Approximately ten pages in length this proposal should describe the aims of the research and provide a broader theoretical framework. After this is approved students begin to conduct individual research in the field or in the library. Students must enroll in a minimum of 8 units

Statistics Subject abbreviation: STAT College of Natural and Agricultural Sciences Daniel R. Jeske, Ph.D., Chair Department Office 2626 Statistics-Computer Building statistics.ucr.edu Business Office (951) 827-3774 Graduate Student Affairs 1140 Batchelor Hall (951) 827-4716 or (800) 735-0717 CNAS Undergraduate Advising Center 1223 Pierce Hall (951) 827-7294 Professors Barry C. Arnold, Ph.D. Subir Ghosh, Ph.D. Daniel R. Jeske, Ph.D. Keh-Shin Lii, Ph.D. Professors Emeriti Robert J. Beaver, Ph.D. D. V. Gokhale, Ph.D. S. James Press, Ph.D. Christopher A. Robertson, Ph.D. David J. Strauss, Ph.D. Associate Professor Xinping Cui, Ph.D. Assistant Professors James M. Flegal, Ph.D. Jun Li, Ph.D. Chi Wang, Ph.D. **

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Lecturers Linda M. Penas, Ph.D. Jill Smith, M.S. Analisa Vega, M.S. Lecturer Emerita Barbara Beaver, M.S.

Major The Department of Statistics is concerned with teaching, research, and statistical consulting. The courses offered present a comprehensive spectrum of statistical and probability theory, in so far as such theory is necessary for the understanding and analysis of observational data. The applications of the theory delineated in the courses may be made in any field of experience. Laboratory classes in which examples related to the student’s actual field of interest are worked out, play an essential part. The department offers both B.A. and B.S. degrees in Statistics as well as a B.S. in Statistics with options in Statistical Computing and Quantitative Management; the M.S. degree in Statistics; and the Ph.D. degree in Applied Statistics. The courses STAT 040, STAT 048, STAT 100A, STAT 100B, STAT 104/BUS 104, STAT 110, STAT 130, STAT 140, STAT 146, and STAT 155 are intended for students of other departments who wish a knowledge of statistical techniques. Some of them may be taken as electives by statistics majors. The objective of these courses is to acquaint the student with the elements of statistics with only the necessary amount of mathematical training. STAT 147 and STAT 157 are computer-oriented courses intended for students who would like to learn about computer programming in the most important languages and who would like to learn about statistical computing. In addition to teaching, the Department of Statistics is responsible to the dean of the College of Natural and Agricultural Sciences and director of the Agricultural Experiment Station for collaboration with research workers in the biological and agricultural fields. A consultative service in the design, analysis, and interpretation of experimental data relating to the agricultural sciences is provided.

Computing Laboratories The Department of Statistics has a strong applied orientation that involves the use of statistical computing while solving real world problems that arise in many disciplines. The department has two interactive multimedia computer laboratories with Pentium-class clients and a SUN Microsystems Netra server, and also has a UNIX-based laboratory that contains multiple SUN Microsystems Blade and Ultra 24 workstations. Each of the labs provides users access to a wide variety of statistical software packages and are networked to both the Internet and the campus WiFi network. The CRAY Supercomputer at the San Diego Supercomputer Center (SDSC) is also available

to faculty and graduate students, as are the 30 PC workstations in a computing laboratory that is maintained by the Statistical Consulting Collaboratory.

Statistical Consulting Center The Statistical Consulting Collaboratory provides a broad range of analytical and statistical support services, including design of experiments, statistical inference, hypothesis testing, and data modeling for the campus community, and promotes cooperative research between statisticians and other investigators in all fields of the application of statistics. The Collaboratory is staffed by a faculty director, two Ph.D. statisticians and graduate students. Daniel R. Jeske, Ph.D., Faculty Director Karen Huaying Xu, Ph.D., Associate Director Scott M. Lesch, Ph.D., Principal Consulting Statistician

University Requirements See Undergraduate Studies section.

College Requirements See College of Natural and Agricultural Sciences, Colleges and Programs section. Some of the following requirements for the major may also fulfill some of the college’s breadth requirements. Consult with a department advisor for course planning.

Major Requirements The department offers both a B.A. and a B.S. degree in Statistics as well as a B.S. in Statistics with options in Statistical Computing and Quantitative Management. The major requirements for the B.A. and the B.S. degrees in Statistics are as follows:

For the Bachelor of Arts 1. Core requirements (24–25 units) a) CS 010, MATH 008B or MATH 009A, MATH 009B, MATH 009C, MATH 010A b) Four (4) additional units in Mathematics, chosen from MATH 113 or MATH 131 2. Upper-division requirements a) Thirty-six (36) units of upper-division course work (1) STAT 147, STAT 155, STAT 157, STAT 170A, STAT 170B (2) Twelve (12) units chosen from STAT 127/BUS 127, STAT 130, STAT 140, STAT 146, STAT 160A, STAT 160B, STAT 160C, STAT 171 (3) Four (4) units of STAT 197 taken at the end of the Senior year Note An introductory Statistics class such as STAT 048, or STAT 100A is strongly recommended.

For the Bachelor of Science 1. Core requirements (24–25 units) a) CS 010, MATH 008B or MATH 009A, MATH 009B, MATH 009C, MATH 010A b) Four (4) additional units in Mathematics, chosen from MATH 113 or MATH 131 2. Upper-division requirements (52 units) a) Thirty-six (36) units of upper-division course work (1) STAT 147, STAT 155, STAT 157, STAT 170A, STAT 170B (2) Twelve (12) units chosen from STAT 127/BUS 127, STAT 130, STAT 140, STAT 146, STAT 160A, STAT 160B, STAT 160C, STAT 171 (3) Four (4) units of STAT 197 taken at the end of Senior year b) Sixteen (16) units of additional course work chosen, with the approval of the major advisor, from Statistics courses numbered 104 and higher or from related fields. Note An introductory Statistics class such as STAT 048, or STAT 100A is strongly recommended. Statistical Computing Option The requirements for this option are in addition to the requirements for the B.S. in Statistics, except that the option requirement takes the place of the 16 units in 2.b) above. 1. Lower-division requirements (8 units): CS 012, CS 014 2. Upper-division requirements (16 units) a) MATH 113 b) Twelve (12) units of course work selected from (1) CS 141, CS 177 (2) MATH 112, MATH 120 (3) STAT 198-I c) MATH 135A, MATH 135B recommended Quantitative Management Option The requirements for this option are in addition to the requirements for the B.S. in Statistics, except that the option requirement takes the place of the 16 units in 2.b) above. 1. Lower-division requirements (16–17 units) a) ECON 003 b) BUS 010, BSAD 020A, BSAD 020B 2. Upper-division requirements (16 units) a) MATH 113 b) Three courses from one area (1) Marketing: BUS 103, BUS 113, BUS 117 (2) Finance: BUS 106/ECON 134, BUS 135A, BUS 135B, BUS 136, BUS 138

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(3) Accounting: BUS 108, BUS 165A, BUS 165B, BUS 168A, BUS 168B (4) Management Information Systems: BUS 101, BUS 171, BUS 173

Minor The minor in Applied Statistics is designed to give students in either the social sciences or the physical sciences a cohesive set of statistics courses to deal with the data analytic aspects of their disciplines and to understand the statistical summaries that are encountered in everyday activities. The requirements for the minor consist of at least 24 and not more than 28 upper-division units in Statistics to include the following: 1. STAT 100A, STAT 100B 2. Eight (8) units from STAT 110, STAT 127/BUS 127, STAT 130, STAT 140, STAT 146 3. Four (4) units from STAT 147, STAT 157 4. Four (4) additional units from 2. or 3. above Of the specified upper-division units, a minimum of 16 must be unique to the minor and may not be used to satisfy major requirements. No more than 4 units may be in courses numbered 190 through 199. See Minors under the College of Natural and Agricultural Sciences in the Colleges and Programs section of this catalog for additional information on minors.

Graduate Programs The Department of Statistics offers the M.S. degree in Statistics and the Ph.D. degree in Applied Statistics. Admission Domestic and international applicants must supply scores from the GRE general exam. In addition, TOEFL scores must be supplied by all applicants whose first language is not English. The department considers applications for teaching assistantships at the same time as those for fellowships. Normally, applications for fellowships are awarded by February or March for students admitted for the following Fall quarter. Students in the Ph.D. program who have satisfied all requirements for the master’s degree may apply for this degree while completing requirements for the Ph.D. program.

Students must also meet the other requirements for admission as specified by the Graduate Division. The program is Plan II (Comprehensive Examination) described in the Graduate Studies section of this catalog. No foreign language is required. Plan II (Comprehensive Examination) Graduate students in Statistics must take (or have taken) appropriate courses in Mathematics to give them the proper background for graduate work in Statistics. Important areas include Calculus (at least MATH 008B or MATH 009A, MATH 009B, MATH 009C, and MATH 010A) and Linear Algebra (at least MATH 131). Students are strongly encouraged to take at least one of the following: MATH 120 (Optimization), MATH 126 (Combinatorics), MATH 135A, MATH 135B (Numerical Analysis), MATH 151A, MATH 151B, MATH 151C (Advanced Calculus), MATH 165A, MATH 165B (Complex Variables), and MATH 209A, MATH 209B, MATH 209C (Real Analysis). The specific courses selected naturally depend on the research area selected by the student. The program consists of a minimum of 36 approved units. These must include 1 unit of STAT 288; 12 units of STAT 293 are counted toward this total. In addition, at least 20 units must be from STAT 200A, STAT 200B, STAT 203A, STAT 203B, STAT 205, STAT 207A, STAT 207B, STAT 210A, STAT 210B, STAT 210C, STAT 215, STAT 216A, STAT 216B, STAT 220A, STAT 220B, STAT 230, STAT 240. Knowledge of at least one computer language and the use of statistical computer packages is required, and students lacking this background should take STAT 157. Early in the program the student submits a program proposal, which requires the approval of the M.S. advisor. The advisor also supervises the student’s progress and course of study. After completion of the required courses, the student takes a written comprehensive examination. This is generally offered twice annually, in the fall and spring quarters. Some students can petition to change their degree objective from the M.S. degree to the Ph.D. program in Applied Statistics depending on their performances in the written comprehensive exam and coursework.

Master’s Program

Students in the Ph.D. program who have satisfied all requirements for the master’s degree may apply for this degree while completing requirements for the Ph.D. program.

The Department of Statistics offers the M.S. degree in Statistics.

Doctoral Degree

Admission Students entering the program must either have completed a bachelor’s degree in Statistics (or the equivalent), or take STAT 160A, STAT 160B, STAT 160C, STAT 161 and STAT 170A, STAT 170B, STAT 171, covering basic areas of probability and statistics. These courses would not be counted as credit towards the master’s degree.

The Department of Statistics offers the Ph.D. degree in Applied Statistics. The program emphasizes both the theory of statistics and its application to special fields of interest. In addition to courses in statistics, a student would take courses in a substantive field from which a thesis problem requiring a statistical approach should arise. The substantive field may be chosen from areas such as

biology, economics, political science, psychology or administration. Specialties might include, for example, population genetics, biological control, hydrology, epidemiology, geology, discrimination in learning, or scales and measurements. Admission Students entering the program must have completed either a bachelor’s degree or a Master’s degree in Statistics, Computer Science, Mathematics, or some other quantitatively based discipline. Students lacking sufficient preparation for some statistics graduate classes must complete some preparatory work in Statistics, Computer Science, or Mathematics depending on their background. Students also have to meet the general requirements listed in the Graduate Studies section of this catalog. Course Work Courses to be taken are in Statistics and the substantive field appropriate to the student’s interest. Students without the courses prescribed by the M.S. in Statistics or their equivalent must take them as soon as possible. Students must complete course work in statistics greater in depth than that required for the M.S. Students must have knowledge of at least one computer language and the use of statistical computer packages; students lacking this background should take STAT 157. They must select four or more additional quarter courses in Statistics at the 200 level, not to be graded “Satisfactory/No Credit.” These additional courses should be selected in consultation with the graduate advisor and/or the student’s major professor in order to strengthen a student’s background in statistics and to prepare the student for thesis work and a career in research and teaching. To be approved, A program must include STAT 210A, STAT 210B, STAT 210C and three of the following five courses: STAT 200A, STAT 203A, STAT 215, STAT 216A, STAT 220A. In preparing for the written qualifying examinations, a student can register for up to 6 units of STAT 291 (Individual Studies in Coordinated Areas) only during quarters that the student actually participates in qualifying examinations. In addition, students must complete a minimum of 12 units (or equivalent) in a substantive field with a minimum GPA of 3.00. The requirement may be waived if the student already has the background in the substantive area. Foreign Language Requirement None Qualifying Examination Before advancement to candidacy, students must demonstrate proficiency on a qualifying examination which is normally taken after two years of course work and seminars. Dissertation The dissertation is pertinent to a problem area specified by the candidate’s substantive field and is submitted in accordance with the requirements of the Graduate Division, Riverside. Teaching Requirement All students in the program, for at least three quarters, assist with laboratory (practice) sections of undergraduate Statistics courses or individual tutorial (consultative) work with undergraduate students.

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Normative Time to Degree 15 quarters

Lower-Division Courses STAT 040. Elements of Statistics (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): none. An introduction to statistics. Adopts the modern Bayesian approach that advocates that estimates, hypothesis tests, and decisions be made from information developed from a formal combination of current and earlier data. Topics include summarizing and displaying data, designing experiments, probability, Bayes’ rule, inferences from proportions and normal populations, sampling, and regression analysis. Uses Minitab. STAT 048. Statistics for Business (5) Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): CS 008 or equivalent; MATH 004 or MATH 005 or MATH 008A or MATH 009A or MATH 9HA or equivalent. An introduction to statistics using business applications. Topics include descriptive statistics, probability, discrete and continuous distributions, Bayes’ theorem, random variables, estimation and confidence intervals, hypothesis testing, analysis of variance, and simple linear regression. Credit is awarded for only one of STAT 048 or STAT 100A.

Upper-Division Courses STAT 100A. Introduction to Statistics (5) Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): MATH 005 or MATH 008A or MATH 009A or MATH 09HA or equivalent. A general introduction to descriptive and inferential statistics. Topics include histograms; descriptive statistics; probability; normal, binomial, and Poisson distributions; sampling distributions; hypothesis testing; and confidence intervals. Credit is awarded for only one of STAT 048 or STAT 100A. STAT 100B. Introduction to Statistics (5) Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): STAT 100A. An introduction to inferential statistics. Topics include linear regression, correlation, analysis of variance, nonparametric methods, and simple experimental designs. STAT 104. Decision Analysis and Management Science (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): CS 008 or equivalent; STAT 048 or STAT 100A or equivalent; upper-division standing. A survey of deterministic and probabilistic models for decision making. Topics include linear programming and extensions, networks, dynamic programming, decision trees, queuing models, and simulation. Explores the application of these models in decision making. Emphasizes use of the computer. Cross-listed with BUS 104. STAT 110. Biostatistical Methods in Life Sciences (5) Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): STAT 100B or consent of instructor. Provides undergraduate students majoring or interested in life sciences with statistical tools for analyzing different types of data frequently encountered in life sciences. Emphasizes applications of methodology, including contingency table analysis, linear regression and ANOVA, maximum likelihood method and the estimation-maximization algorithm, logistic regression, Poisson regression, and survival analysis. STAT 127. Introduction to Quality Improvements (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 048 or STAT 100A or consent of instructor. Explores Deming’s 14 points for management,

graphical methods, fishbone diagram, Pareto analysis, control charts for attributes and variables, cusum and moving average charts, process-capability, economic design, acceptance sampling, Taguchi method, parameter design, tolerance design, reliability, hazard rate, censoring, and accelerated life testing. Cross-listed with BUS 127.

STAT 161. Introduction to Probability Models (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A and STAT 160B, or equivalent. Compound distributions. Branching processes. Random walk. Continuous time models; Poisson process, queuing models. The Markov property. Introduction to Markov chains. Simple time series models.

STAT 130. Sampling Surveys (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100A, STAT 100B, or equivalents. Simple random sampling. Stratified sampling. Cluster sampling. Ratio and regression estimates. Random response, capturerecapture and jack-knife techniques.

STAT 170A. Regression Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 147, STAT 155, STAT 157, or equivalents. Topics include simple and multiple linear regression; scatter-plots; point and interval estimation; prediction; testing; calibration; interpretation and practical applications of multiple regression; simple, partial, and multiple correlation; variable selection methods; diagnostic procedures; and regression for longitudinal data.

STAT 140. Nonparametric Techniques (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100B or equivalent. Covers randomization tests, rank tests, methods of association, and distributionfree tests. STAT 146. Statistical Forecasting Techniques (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100B or equivalent. Topics include exponential smoothing, simple and multiple regression analysis, time series, trend analysis, and seasonal analysis. STAT 147. Introduction to Statistical Computing (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 040 or equivalent. Introduction to computerassisted data analysis and statistical inference using both the MINITAB and SAS packages. Topics include input, output, and editing of data; graphical procedures; descriptive statistics; cross-tabulation; inferential statistical techniques including estimation and testing; regression; and analysis of variance. STAT 155. Probability and Statistics for Science and Engineering (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 009C or MATH 09HC (MATH 009C or MATH 09HC may be taken concurrently). Covers sample spaces and probability; random variables and probability distributions; elements of statistical inference; and testing and estimation. Also addresses selected topics in multivariate distributions and introduces stochastic processes. STAT 157. Statistical Computer Packages (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100A, STAT 100B, or equivalents; STAT 147; or consent of instructor. A study of major statistical packages, including SAS and BMPD with the emphasis on advanced SAS programming. Topics include advanced graphical procedures, linear models (regression and analysis of variance), multivariate techniques, and SAS macros. STAT 160A. Elements of Probability and Statistical Theory (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 009C or MATH 09HC (may be taken concurrently). Topics include statistical regularity, probability spaces, fundamental theorems in discrete probability, Bayes’ theorem, random variables, densities and distribution functions, continuous distributions, transformations of random variables, and central limit theorem. Credit is awarded for only one of MATH 149A or STAT 160A. STAT 160B. Elements of Probability and Statistical Theory (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A. Topics include distributions of sample statistics, statistical inference, and estimation. Credit is awarded for only one of MATH 149B or STAT 160B. STAT 160C. Elements of Probability and Statistical Theory (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160B. Topics include hypothesis testing, chi-square tests, and nonparametric methods. Credit is awarded for only one of MATH 149C or STAT 160C.

STAT 170B. Design of Experiments (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 170A. Topics include principles of design; completely randomized designs and one-way analysis of variance; complete block designs and two-way analysis of variance; multiple comparisons; complete factorial experiments; fixed, random, and mixed models; split-plot designs; nested designs; analysis of covariance; sample size determination and power analysis. STAT 171. General Statistical Models (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 170B. Generalized linear models and least squares. Analysis of covariance, nonlinear regression, nonlinear least squares. Regression methods for discrete data: loglinear models, logistic regression, discriminant analysis. Regression methods for life data. Cox survival model, Kaplan-Meier estimation, MantelHaenszel test. STAT 190. Special Studies (1-5) hours to be arranged. To be taken with the consent of the chair of the department as a means of meeting special curricular problems. Course is repeatable to a maximum of 10 units. STAT 197. Research for Undergraduates (2-4) Outside research, 3-6 hours; individual study, 3-6 hours. Prerequisite(s): upper-division standing or consent of instructor. An introduction to research in Statistics. Requires a research project completed under the supervision of a Statistics faculty member or a group of faculty members. Students who make an oral presentation of the research project or submit a written research report receive a letter grade; other students receive a Satisfactory (S) or No Credit (NC) grade. Course is repeatable as research topic changes to a maximum of 8 units. STAT 198-I. Individual Internship in Statistics (1-12) Internship, 2-24 hours; outside research, 1-12 hours. Prerequisite(s): STAT 100B, consent of instructor, upper-division standing. An internship to provide statistical field experience in governmental, industrial, or research units. Projects must be approved by the Statistics Department and the head of the unit in which the internship is to be carried out. Requires a written report. Graded Satisfactory (S) or No Credit (NC). Course is repeatable to a maximum of 16 units, but total credit toward graduation may not exceed 12 units. STAT 199H. Senior Honors Research (1-5) Prerequisite(s): senior standing with major concentration in statistics and with consent of instructor. Senior standing with major concentration in statistics and with consent of instructor. Course is repeatable to a maximum of 10 units.

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Graduate Courses

for the degree receive a letter grade; other students receive a letter grade or petition for a Satisfactory (S) or No Credit (NC) grade.

applications from finite populations, nonsampling errors, estimation of response bias and of optimum number of interviewers, and sampling inspection.

STAT 200A. Advanced Design and Analysis of Experiments (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 170A, STAT 170B, STAT 171, or equivalents. Topics include fixed, mixed, and random effects models; complete and incomplete block designs; row-column designs; nested designs; split-plot designs; crossover designs; analysis of covariance; repeated measure designs; and optimality of designs.

STAT 209B. Statistical Data Mining (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 209A; or consent of instructor. Introduces principle data-mining methodologies, major software tools, and typical applications for structuring, understanding, and using large datasets effectively and efficiently. Statistics graduate students who have not completed all courses required for the degree receive a letter grade; other students receive a letter grade or petition for a Satisfactory (S) or No Credit (NC) grade.

STAT 231A. Statistics for Biological Sciences (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 023, STAT 100A, STAT 100B, or equivalents, or consent of instructor. Topics include one- and twosample tests, one- and two-way analysis of variance, multiple comparison, simple and multiple linear regression, nonparametric statistics, and categorical data. Statistics graduate students who have not completed all courses required for the degree receive a letter grade; other students receive a letter grade or petition for a Satisfactory (S) or No Credit (NC) grade.

STAT 210A. Theoretical Statistics and Probability (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 010B, STAT 160C, or equivalents. Topics include conditional probability, independence, distribution functions, generating functions, convergence concepts, limit theorems, and order statistics.

STAT 231B. Statistics for Biological Sciences (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 231A or consent of instructor. Topics include logistic regression, analysis of covariance, advanced experimental designs, randomization, bootstrapping, jackknifing, and other procedures. Statistics graduate students who have not completed all courses required for the degree receive a letter grade; other students receive a letter grade or petition for a Satisfactory (S) or No Credit (NC) grade.

STAT 200B. Advanced Design and Analysis of Experiments (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 170A, STAT 170B, STAT 171, or equivalents; STAT 200A. Topics include factorial experiments; confounding and fractional factorial experiments for symmetrical and asymmetrical factorial experiments; orthogonal and balanced arrays; optimal fractional factorial designs; first and second order response surface designs; rotatibility; and blocking of response surface designs; method of steepest ascent; canonical representation; and minimum bias, variance, and mean square error designs. STAT 203A. Bayesian Statistics I (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160C or equivalent. Subjective probability, Renyi axiom system, Savage axioms, coherence, Bayes theorem, credibility intervals, Lindley paradox, empirical Bayes estimation, natural conjugate priors, de Finetti’s theorem, approximation methods, Bayesian bootstrap, Bayesian computer programs. STAT 203B. Bayesian Statistics II (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 203A. Assessing priors, nonparametric density estimation for expert group judgements, Bayesian regression, Bayesian analysis of variance, Bayesian regression with correlated disturbances and heteroscedasticity, Bayesian inference in time series models, Bayesian classification, Bayesian inference in spatial statistics, Bayesian factor analysis, disputed authorship. STAT 205. Discrete Data Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C or equivalents; or consent of instructor. Contingency tables, log-linear models, information theory models, maximum likelihood estimation, goodness of fit, measures of association, computational procedures. STAT 207A. Statistical Computing (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C, STAT 170A, STAT 170B; or consent of instructor. Topics include computational aspects of least squares in linear statistical models, optimization in nonlinear statistical models, numerical accuracy and error analysis, simulations and Monte Carlo methods for problems in statistical inference, pseudorandom numbers, and numerical approximations. STAT 207B. Statistical Computing (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C, STAT 170A, STAT 170B; or consent of instructor. Topics include resampling methods, expectation maximization (EM) algorithm, Markov chain and Monte Carlo methods, and other current computational methods. STAT 209A. Statistical Data Mining (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 170A; or consent of the instructor. Introduces principal data-mining methodologies, major software tools, and typical applications for structuring, understanding, and using large datasets effectively and efficiently. Statistics graduate students who have not completed all courses required

STAT 210B. Theoretical Statistics and Probability (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 210A. Topics include estimation, decision theory, Bayes and empirical Bayes rules, and efficiency. STAT 210C. Theoretical Statistics and Probability (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 210B. Topics include hypothesis testing, sequential inference, distributions, and free and robust techniques. STAT 215. Stochastic Processes (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C, STAT 161. The Markov property; Markov chains; Markov processes and Poisson processes. Birth and death models. Queues. Random walks. Renewal processes. Wiener processes and diffusion. STAT 216A. Time Series Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C, STAT 161, or equivalents. Topics include stationary processes, autoregressive—moving average (ARIMA) processes, trend, seasonality, model building, estimation and forecasting, and spectral analysis and estimation. STAT 216B. Time Series Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 216A or consent of instructor. Topics include spectral analysis and estimation, higher-order spectral analysis, Kalman filtering and prediction, and nonlinear, nonstationary, and non-Gaussian time series. STAT 220A. Multivariate Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C, or equivalents; familiarity with matrix algebra. Topics include algebra and calculus of vectors and matrices, special multivariate distributions (Normal, Wishart, Hotelling’s T-squared, multivariate T, multivariate log-normal, etc). STAT 220B. Multivariate Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 220A or consent of instructor. Topics include categorical dependent variable regression, loglinear models, inference in the multivariate normal distribution, multivariate multiple regression, hypothesis testing, likelihood ratio tests, multivariate analysis of variance and covariance, principal components analysis, factor analysis, and classification and discrimination models. STAT 230. Sampling Theory (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160C. Covers the theory of stratified, ratio, and regression methods of estimation and cluster and double sampling. Includes the concept of sufficiency and its

STAT 240. Nonparametric Methods (4) Lecture, 3 hours; consultation, 1 hour. Prerequisite(s): STAT 160A, STAT 160B, STAT 160C. Theory of distributionfree statistics, ranking statistics, rank correlation, Ustatistics. Nonparametric point and interval estimation. Empirical distribution function methods. Combinatorial problems; runs, matching, occupancy; limiting distributions. STAT 251. Statistics Colloquium (1) Colloquium, 1.5 hours. Prerequisite(s): consent of instructor. Presentation of current research in statistics by faculty, advanced graduate students, and guest lecturers. Graded Satisfactory (S) or No Credit (NC). Course is repeatable. STAT 255 (E-Z). Seminar on Topics in Applied Statistics (3-4) Seminar, 3 hours; discussion, 1 hour. Prerequisite(s): graduate standing. Additional prerequisites are required for some segments of this course; see department. Discussions and lectures by graduate students and faculty on topics related to student and faculty research. In some courses students will receive letter grades only. In others students may receive either a letter grade or Satisfactory (S) or No Credit (NC) grade; no petition is required, but students must see instructor for grading basis. The department will maintain a listing of all 255 segments and their unit value and grading basis. Normally graded Satisfactory (S) or No Credit (NC), but students may petition the instructor for a letter grade on the basis of assigned extra work or examination. STAT 288. Literature Seminar (1) Seminar, 1 hour. Students will make oral presentations summarizing important research papers in the statistics literature. All graduate students are encouraged to participate. Topics may vary each term. Graded Satisfactory (S) or No Credit (NC). STAT 290. Directed Studies (1-6) Prerequisite(s): graduate standing and consent of instructor. Individual studies on specially selected topics in statistical applications. Graded Satisfactory (S) or No Credit (NC). Course is repeatable. STAT 291. Individual Studies in Coordinated Areas (1-6) Consultation, 1-6 hours. Prerequisite(s): graduate standing. A program of studies designed to assist candidates who are preparing for examinations. Open to M.S. and Ph.D. students; does not count toward the unit requirement for the M.S. degree. Graded Satisfactory (S) or No Credit (NC). May be repeated for credit.

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STAT 292. Concurrent Analytical Studies (1-4) Outside research, 3-12 hours. Prerequisite(s): consent of instructor and concurrent enrollment in 100-series course. To be taken on an individual basis. Student will complete a graduate paper related to the 100series course. Graded Satisfactory (S) or No Credit (NC). May be repeated for credit. STAT 293. Statistical Consulting and Data Analysis (4) Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 160C, STAT 170B, STAT 171; or consent of instructor. Covers statistical consulting and analysis of client data, the client-consultant meeting, negotiations, communications, interactions, and skills that facilitate the process of self-learning. Involves client visitations and field trips. Students present written and oral reports and technical talks. Statistics graduate students receive a letter grade; other students receive a letter grade or Satisfactory (S) or No Credit (NC) grade. Course is repeatable to a maximum of 12 units. STAT 297. Directed Research (1-6) Prerequisite(s): graduate standing and consent of instructor. Directed research in applications of statistics in biological studies, including computer simulation. Graded Satisfactory (S) or No Credit (NC). STAT 299. Research for Thesis or Dissertation (1-12) Prerequisite(s): graduate standing and consent of instructor. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

Professional Course STAT 302. College Teaching Practicum (1-4) Practicum, 3-12 hours. Prerequisite(s): graduate standing and consent of instructor. Required of all teaching assistants in the department. Credit not applicable to graduate unit requirements. Supervised teaching in college level classes under the supervision of the course instructor. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.

Theatre Subject abbreviation: THEA College of Humanities, Arts, and Social Sciences

Major The Department of Theatre offers a B.A. in Theatre. The major focuses on three broad areas of theatre — its literature, history, and criticism; performance, design, direction, and technology; and the elements of production. Students have the opportunity to write, perform, direct, and design. Four stages are available for rehearsals and performances: the 500seat proscenium University Theatre, the new 150-seat Studio Theatre in the Arts building with state-of-the-moment equipment for facilities, the 120-seat Rehearsal Lab, and the 50seat Barn Theatre. Students are able to practice acting in facultydirected shows, student productions, and class presentations. Special projects and studies are offered for advanced students to produce an original work or to study in more depth acting, directing, scenic design, or playwriting. As part of the Theatre Department’s ongoing goal to provide a comprehensive and world-class program in the performing arts, a new Writing Track has been created for students who are primarily interested in pursuing the goal of writing for the performing arts. In addition to taking classes in playwriting and screenwriting, students will be able to take advantage of the department’s active production environment, which is a necessary component of any playwriting or screenwriting education. As Theatre majors in a writing track, student playwrights and screenwriters will be able to take classes in writing for the performing arts, acting, directing, and other production classes as requirements rather than having to fit them in as often-unavailable electives. Student assistantships, work-study, Gluck Fellowships, and scholarships such as the Chancellor’s Performance Award are available to students. For further information or a department tour, call the Theatre Department, (951) 827-3343.

University Requirements

2. Performance, Direction, Playwriting, Screenwriting, Design, and Theatre Technology requirement a) THEA 101, THEA 102, THEA 109 b) Twelve (12) units from THEA 110A, THEA 110B, THEA 111A, THEA 111B, THEA 112E, THEA 113 (E-Z), THEA 132, THEA 133, THEA 135, THEA 141, THEA 142, THEA 143, THEA 144, THEA 145, THEA 150A, THEA 150B, THEA 164A/CRWT 164A, THEA 164B/CRWT 164B, THEA 164C/CRWT 164C, THEA 166A/CRWT 166A/MCS 166A, THEA 166B/CRWT 166B/MCS 166B, THEA 166C/CRWT 166C/MCS 166C, THEA 176/ANTH 128/AST 128/ DNCE 128/MUS 128, THEA 180 (E-Z) 3. Production requirement Twelve (12) units of THEA 170 with two (2) units from each of the following areas: sets, costumes, and lighting/sound. Six of these units must be taken in residence. Track 2: Writing for the Performing Arts Upper-division requirements (66 units) 1. THEA 100, THEA 101, THEA 109, THEA 170 (2 units) 2. Literature, History, Criticism (16) units from CPLT 146, CPLT 149, ENGL 117A, ENGL 117B, ENGL 117C, ENGL 117T, ENGL 129A, ENGL 129B, ENGL 129C, THEA 120A, THEA 120B, THEA 120C, THEA 121 3. Performance, Playwriting, Screenwriting, Production (24) units from THEA 164A, THEA 164B, THEA 164C, THEA 166A, THEA 166B, THEA 166C 4. Twelve (12) additional units from CRWT 172, THEA 110A, THEA 110B, THEA 150A, THEA 150B, THEA 165A, THEA 165B, THEA 198-I

See Undergraduate Studies section. D. Eric Barr, M.F.A., Chair Department Office, 121 Arts (951) 827-3343; theatre.ucr.edu Professors D. Eric Barr, M.F.A. Richard Hornby, Ph.D. Professor Emeritus Richard D. Risso, Ph.D. Associate Professors Rickerby Hinds, M.F.A. Robin Russin, M.F.A. Haibo Yu, M.F.A. Assistant Professors Charles Evered, M.F.A. Erith Jaffe-Berg, Ph.D. Stuart Krieger, B.A. Keun-Pyo Park, M.F.A. ** Lecturers Bonnie Cherrie, M.F.A. Glen Dunzweiler, M.F.A. Marc L. Longlois, M.F.A.

College Requirements See College of Humanities, Arts, and Social Sciences, Colleges and Programs section.

Major Requirements The major requirements for the B.A. degree in Theatre are as follows: Track 1: General Theatre Upper-division requirements (64 units) 1. Literature, History, Criticism requirement a) THEA 100, THEA 120A, THEA 120B, THEA 120C b) Twelve (12) units from THEA 121, THEA 122, THEA 124A, THEA 124B, THEA 125 (E-Z), THEA 126A, THEA 126B, THEA 127, THEA 191 (E-Z), or any other course in dramatic literature approved by the Chair

Minor The minor in Theatre follows the structure of the major requirements by exposing students to each of the areas that are essential to the creation of theatre, with the opportunity to take an additional course for depth or more exposure. The inclusion of THEA 170 (Advanced Dramatic Production) gives the students the opportunity to put course work into the proper context and provides them with a practical understanding of the workings and problems of production. The minor in Theatre provides students with a basic understanding in major areas of study including theatre literature, performance, and design. It also introduces the nonmajor to the discipline of Theatre, providing breadth for those students majoring in unrelated disciplines.

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