Courses
Courses in the first list are offered each year and are intended mainly
for undergraduates and for graduate students from disciplines other than
statistics.
20000. Elementary Statistics
22000. Statistical Methods and Their Applications
22200. Linear Models and Experimental Design
22400. Applied Regression Analysis
22600. Analysis of Qualitative Data
22700. Biostatistical Methods
24000. Probability and Statistics in the Natural Sciences
24100. Probability and Statistics in the Natural Sciences (50 unit course)
24200. Applied Probability and Stochastic Models
23400, 23500 Statistical Models and Methods I, II
24400, 24500, 24600. Statistical Theory and Methods
25100. Introduction to Mathematical Probability
26700. History of Statistics
Development of probability theory and its use in science to quantify uncertainty
in observational data and as a conceptual framework for scientific theories.
Courses in the second list are offered each year or in alternate years
and are intended,
primarily but not exclusively, for graduate students in statistics.
30100, 30200. Mathematical Statistics
The mathematical structure of statistics; parameter estimation, efficiency,
confidence sets, tests of hypotheses, Bayesian analysis, decision theory
and asymptotic methods.
30400. Distribution Theory
Deriving, characterizing, displaying and approximating distributions.
Computer-based algebra; Edgeworth, saddlepoint, and Laplace approximations.
30700. Numerical Computation
Numerical algorithms, particularly in linear systems.
31200. Introduction to Stochastic Processes I
Branching processes, recurrent events, renewal theory, random walk, Markov
chains, Poisson and birth-and-death processes.
31300. Introduction to Stochastic Processes II
Continuation of 31200, focusing on continuous time Markov chains, and
martingales.
32000. Bayesian Statistics
Basic concepts and methods; recent advances in computational techniques:
asymptotic approximation, Bayesian data analysis.
33100. Sample Surveys
Random sampling methods; stratification, cluster sampling, ratio estimation;
methods for dealing with non-response and partial response.
34300. Applied Linear Statistical Methods
The theory, methods and applications of fitting and interpreting multiple
regression models.
34500. Design and Analysis of Experiments
Linear models in experimental design: blocking, randomization, fractionation
and confounding, fixed and random effects; analysis of designed experiments.
34700. Generalized Linear Models symmetric functions, Edgeworth and saddlepoint
approximations.
32200. Applied Bayesian Data Analysis
32300. Analysis of Incomplete Data
33200. Survey Topics
33400. Applied Forecasting
33500. Time Series Analysis
33900. Spatial Statistics
34600. Multivariate Methodology and Data Analysis
34900. Applied Nonparametric Statistics
35000. Fundamentals of Epidemiology
Exponential-family models and variance functions; logistic regression,
log-linear models. Quasi-likelihood, least squares and partially linear
models.
36700. History of Statistics
Development of probability theory and its use in science to quantify uncertainty
in observational data and as a conceptual framework for scientific theories.
38100–38300. Measure-Theoretic Probability
A rigorous treatment of probability including a development of measure
theory: existence theorems, integration and expectation, characteristic
functions, limit laws, Radon-Nikodym derivatives, conditional probabilities,
martingales, Brownian Motion.
39000, 39100. Stochastic Calculus and Finance I, II
An introduction to probability theory and stochastic calculus integrated
with the use of those tools for valuing and hedging derivative securities.
44100. Consulting in Statistics
The third list includes advanced or specialized courses that have been
taught in the past years. Each year a selection similar to these are offered,
depending on the current interests of the faculty and students.
30500. Theoretical Statistics
The foundations of statistical inference; the likelihood principle, sufficiency
and conditionality principles, Bayesian and frequency-based inferences.
31400. Tensor Methods in Statistics
Multivariate moments and cumulants, set partitions and M^bius inversion,
k-statistics and 35100. Advanced Epidemiology
35500. Statistical Genetics
Mapping of human disease genes and genetic markers; statistical and computational
problems in the analysis of big pedigrees with complex genetic models.
35600. Introduction to Survival Analysis
35700. Resampling Methods
Bootstrapping, jackknifing and cross-validation; comparison to analytic
techniques; applications.
36300. Topics in Likelihood Theory
36500. Statistical Decision Theory36900. Robust Estimation
The theory of M-estimators and linear functions of order statistics; history
of robust inference, rejection of outliers, influence functions.
37500. Topics in Bayesian Analysis
37700. Simulation Methods
Random number generation, sampling from special distributions, Monte Carlo
integration techniques, importance weighting, Gibbs sampling.
37800. Statistical Computation
37900. Computer Vision
38500. Advanced Probability: Stochastic Calculus
38600. Advanced Probability: Weak Convergence
38900. Probability and Finance
39200. Spectral Methods in Statistics
Fourier theory, computation, and applications to spectroscopy and imaging.
Wavelets.
39300. Reading Fisher
39500. Nonparametric Regression and Classification
39600. Inference for Dependent Processes
39900. Master’s Seminar
45100. Workshop in Statistics
45500. Statistical Genetics (50 unit course)
45600. Workshop in Genetics
46100. Asymptotics in Inference (50 unit course)
46300. Topics in Statistical Inference (50 unit course)
47000. Conceptual Issues in Inference (50 unit course)
47800. Statistical Algorithms (50 unit course)
48800. Workshop on Shrinking Interval Asymptotics
49200. Wavelets (50 unit course)
49300. Workshop in Financial Engineering
49400. Workshop in Statistics and Finance
49500. Nonparametric Regression (50 unit course)
49700. The Craft of Research (50 unit course)
This list was last revised on 9/02/2003.
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