UCR

Statistics



Graduate Courses


Graduate Courses


  • Statistics 200A-B - Advanced Design and Analysis of Experiments
    4 Units
    Lecture, three hours; discussion, one hour
    Prerequisite(s): Statistics 170A-170B, 171 or equivalent
    (A) 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.
    (B) Topics include factorial experiments confounding and fractional factorial experiments for symmetrical and asymetrical 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.
  • Statistics 201A-B-C - Theory of Probability and Statistics
     4 Units
    Lecture, three hours; discussion one hour
    Prerequisite(s): Math 010B; Statistics 160C or equivalent; graduate standing; or consent of instructor.

    (A) Topics include probability and conditional probability; random variables: univariate and multivariate; distributions; independence; moments; generating functions; transformations, and standard distributions. Also addresses multivariate normal distribution; order statistics; inequalities; convergence concepts; law of large numbers, and the central limit theorem. Credit is not awarded for STAT201A, if it has already been awarded to STAT210A if STAT210A was taken prior to Fall 2013.
    (B) Topics include exponential families; delta method; inference concepts; sufficiency; point estimation; unbiasedness; completeness; and consistency. Also explores relative efficiency; maximum likelihood; method of moments; interval estimation; pivotals; and approximate intervals and regions. Credit is not awarded for STAT201B, if it has already been awarded to STAT210B if STAT210B was taken prior to Fall 2013.
    (C) Topics include Bayesian estimation; prior selection; loss functions;
    admissibility; hypothesis testing; Neyman-Pearson lemma; size; power; UMP tests; likelihood ratio tests; sequential tests; non-parametric tests; and bootstrap. Credit is not awarded for STAT201C, if it has already been awarded to STAT210C if STAT210C was taken prior to Fall 2013.

  • Statistics 203A-B -Bayesian Statistics I and II
    4 Units
    Lecture, three hours; discussion one hour
    Prerequisite(s): Statistics 160C or equivalent
    (A) 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.
    (B) 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.
  • Statistics 205 - Discrete Data Analysis
    4 Units
    Lecture, three hour; discussion, one hour
    Prerequisite(s): Statistics 160A-B-C or equivalent, or consent of instructor
    Contingency tables, log-linear models, information theory models, maximum likelihood estimation, goodness of fit, measures of association, computational procedures.
  • Statistics 207 - Statistical Computing
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s): Statistics 201A, or consent of instructor.
    Topics include computational aspects of optimization; numerical integration; Monte Carlo methods; resampling methods; expectation maximization (EM) algorithm; Markov chain and Monte Carlo methods; nonparametric estimation; and other current computational methods.
  • Statistics 209A-B - Statistical Data Mining
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s): STAT 160A, STAT 160B, STAT170; 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 210A-B - Advanced Theory of Probability and Statistics
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s):graduate standing; STAT 201C or equivalent; or consent of instructor.
    (A) Topics include measure spaces; measure integration; convergence
    theorems; absolute continuity; product spaces; Tonelli-fubini theorems; convolutions and transforms; probability spaces; and existence and extension theorems. Also covers inequalities; independence; conditional probability and expectation; convergence concepts; laws of large numbers; weak convergence; and central limit theorem. Credit is not awarded for STAT 201A if it has already been awarded to STAT 210A if STAT 210A was taken prior to Fall 2013.
    (B) Topics include estimation, decision theory, Bayes and empirical Bayes rules, and efficiency. Prerequisite: STAT210A. Credit is not awarded for STAT 201B if it has already been awarded to STAT 210B if STAT 210B was taken prior to Fall 2013.
  • Statistics 215 - Stochastic Processes
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s): Statistics 160A-B-C; Statistics 161.
    The Markov property; Markov chains; Markov processes and Poisson processes. Birth and death models. Queues. Random walks. Renewal processes. Wiener processes and diffusion.
  • Statistics 216A-B - Time Series Analysis
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s): Statistics 160A-160B-160C, 161
    (A) Topics include stationary processes, autoregressive--moving average (ARIMA) processes, trend, seasonality, model building, estimation and forecasting, and spectral analysis and estimation.
    (B) Topics include spectral analysis and estimation, higher-order spectral analysis, Kalman filtering and prediction, and nonlinear, nonstationary,
    and non-Gaussian time series. Prerequisite: STAT216A or consent of instructor.
  • Statistics 220A-B- Multivariate Analysis
    4 Units
    Lecture, three hours.
    Prerequisite(s): Statistics 160A-160B-160C or equivalent plus familiarity with matrix algebra.
    (A) Topics include algebra and calculus of vectors and matrices, special multivariate distributions (Normal, Wishart, Hotelling's T-squared, multivariate T, multivariate log-normal, etc).
    (B) 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. Prerequisite: STAT 220A or consent of instructor.
  • Statistics 230 - Sampling Theory
    4 Units
    Lecture, three hours.
    Prerequisite(s): Statistics 160C.
    Covers the theory of stratified, ratio, and regression methods of estimation and cluster and double sampling. Includes the concept of sufficiency and its applications from finite populations, nonsampling errors, estimation of response bias and of optimum number of interviewers, and sampling inspection.
  • Statistics 231A-B - Statistics for Biological Sciences
    4 Units
    Lecture, three hours; discussion, one hour.
    Prerequisite(s): Math 023,  100B or equivalent, or consent of the instructor.
    (A) Covers one- and two-sample tests, one- and two-way analysis of variance, multiple comparisons, simple and multiple linear regression, nonparametric statistics, and categorical data.
    (B) Covers logistic regression, analysis of covariance, advanced experimental designs, randomization, bootstrapping, jackknifing, and other procedures. Prerequisites: MATH 031, or equivalent; STAT 231A or consent of instructor; graduate standing in Biochemistry and Molecular Biology; Biomedical Sciences; Botany; Cell, Molecular, and Developmental Biology; Entomology; Environmental Toxicology; Genetics, Genomics, & Bioinfomatics; Evolution, Ecology, and Organismal Biology; Microbiology; Nematology; Neuroscience; Plant Biology; Plant Genetics; Plant Pathology; Plant Science.
  • Statistics 240 - Nonparametric Methods
    4 Units
    Lecture, three hours; consultation, one hour.
    Prerequisite(s): Statistics 160A-B-C.
    Theory of distribution-free statistics, ranking statistics, rank correlation, U-statistics. Nonparametric point and interval estimation. Empirical distribution function methods. Combinatorial problems; runs, matching, occupancy; limiting distributions.
  • Statistics 251 - Statistics Colloquium
    1 Unit
    Seminar, one and one-half hours.
    Presentation of current research in statistics by faculty, advanced graduate students and guest lecturers. Grades will be Satisfactory (S) or No Credit (NC).
  • Statistics 255 (E-Z) - Seminar on Topics in Advanced Statistics
    3-4 Units
    Seminar, three hours; discussion, one hour.
    Prerequisite(s): graduate standing.
    Discussions and lecturers 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.
  • Statistics 288 - Literature Seminar
    1 Unit
    Seminar, one 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. To be graded Satisfactory (S) or No Credit (NC).
  • Statistics 290 - Directed Studies
    1-6 Units
    Hours to be arranged
    Prerequisite(s): graduate standing and consent of instructor.
    Individual studies on specially selected topics in statistical applications. To be graded Satisfactory (S) or No Credit (NC). Course is repeatable.
  • Statistics 291 - Individual Studies in Coordinated Areas
    1-6 Units
    Consultation, one to six 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. To be graded Satisfactory (S) or No Credit (NC). May be repeated for credit.
  • Statistics 292 - Concurrent Analytical Studies
    1-4 Units
    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 100-series course. To be graded Satisfactory (S) or No Credit (NC). May be repeated for credit.
  • Statistics 293 - Methods in Applied Statistics
    4 Units
    Lecture, 3 hours; discussion, 1 hour.
    Prerequisite(s): Statistics 160C, 170B, 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 student receive a letter grade or S/NC. Course is repeatable to a maximum of 12 units.
  • Statistics 297 - Directed Research
    1-6 Units
    Prerequisite(s): graduate standing and consent of instructor.
    Directed research in applications of statistics in biological studies, including computer simulation. To be graded Satisfactory (S) or No Credit (NC).
  • Statistics 299 - Research for Thesis or Dissertation
    1-12 Units
    Prerequisite(s): graduate standing and consent of instructor.
    To be graded Satisfactory (S) or No Credit (NC). Course is repeatable.
  • Statistics 302 - College Teaching Practicum
    1-4 Units
    Practicum, three to twelve 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. Course will be graded Satisfactory (S) or No Credit (NC).

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