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STAT
110: CHANCE:
AN INTRODUCTION TO STATISTICS (Y)
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Prerequisite: None.
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Introductory
statistics and probability, visual methods for summarizing quantitative
information, basic experimental design and sampling methods, ethics and
experimentation, causation, and interpretation of statistical analyses.
Applications will use data drawn from current scientific and medical
journals, newspaper articles and the Internet's World-Wide-Web. Credits
earned in this course may be counted toward the College's natural science
area requirements. STAT 110 may not be used to fulfill the Statistics
requirement for undergraduate admission to the McIntire School of Commerce.
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STAT 112: INTRODUCTION TO STATISTICS (Y)
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Prerequisite: None.
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Graphical
displays of data, relationships in data, design of experiments, causation, random
sampling, probability distributions, inference, confidence intervals, tests
of hypotheses, regression and correlation. Credits earned in this course
may be counted toward the College's natural science area requirements. STAT
112 is a prerequisite for undergraduate admission to the McIntire School of
Commerce.
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STAT 212: INTRODUCTION TO STATISTICAL ANALYSIS
(Y)
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Prerequisite: MATH 121, or permission of
instructor.
Co-requisite: Concurrent enrollment in a
discussion section of STAT 212.
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Introduction
to the probability and statistical theory underlying the estimation of
parameters and testing of statistical hypotheses, including those arising
in the context of simple and multiple regression models. Students will use
computers and statistical programs to analyze data. Examples and
applications are drawn from economics, business, and other fields. Students
will not receive credit for both STAT 212 and ECON 371.
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STAT 301: STATISTICAL COMPUTING AND GRAPHICS
(Y)
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Prerequisite: STAT 110 or STAT 112 or
permission of the instructor.
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An
introduction to statistical computing using S-PLUS. Descriptive statistics
for continuous and categorical variables, methods for handling missing
data, basics of graphical perception, graphical displays, exploratory data
analysis, the simultaneous display of multiple variables. Students should
be experienced with basic text-editing and file manipulation on either a PC
or a UNIX system, and with either a programming language (e.g. BASIC) or a
spread-sheet program (e.g. MINITAB or EXCEL).
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STAT 313: DESIGN AND ANALYSIS OF SAMPLE SURVEYS
(E)
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Prerequisite:
STAT 500 or STAT
110 or STAT 112 or MATH 312, or permission of instructor.
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Discussion
of the main designs and estimation techniques used in sample surveys:
simple random sampling, stratification, cluster sampling, double sampling,
post-stratification, ratio estimation. Nonresponse problems and measurement
errors will also be discussed. Many properties of sample surveys will be
developed through simulation procedures. The SUDAAN software package for
analyzing sample surveys will be used.
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STAT 500: INTRODUCTION TO APPLIED STATISTICS
(Y)
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Prerequisite: Permission of the instructor.
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An introduction
to estimation and hypothesis testing in applied statistics, especially the
medical sciences. Measurement issues, measures of central tendency and
dispersion, probability, discrete probability distributions (binomial and
Poisson), continuous probability distributions (normal, t, chi-square, and
F), and one- and two-sample inference, power and sample size calculations,
introduction to non-parametric methods, one-way ANOVA and multiple
comparisons. Students must also enroll in STAT 598 for 1 unit.
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STAT 512: APPLIED LINEAR MODELS (Y)
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Prerequisite: STAT 500 or MATH 312 or 510, or
permission of instructor.
Co-requisite: Concurrent enrollment in STAT
598.
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Linear
regression models, inferences in regression analysis, model validation,
selection of independent variables, multicollinearity, influential
observations, autocorrelation in time series data, polynomial regression,
nonlinear regression, and other topics in regression analysis.
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STAT 513: APPLIED MULTIVARIATE STATISTICS (Y)
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Prerequisites: STAT 500 and MATH 351 and MATH
312 or 510, or permission of instructor.
Co-requisite: Concurrent enrollment in STAT
598.
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Matrix
algebra, random sampling, multivariate normal distributions, multivariate
regression, MANOVA, principal components, factor analysis, discriminant
analysis. Statistical software, such as SAS or S-PLUS, will be utilized.
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STAT 514: SURVIVAL ANALYSIS AND RELIABILITY
THEORY (SI)
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Prerequisite: STAT 500 or MATH 312 or 510, or
permission of instructor.
Co-requisite: Concurrent enrollment in STAT
598.
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Lifetime
distributions, hazard functions, competing-risks, proportional hazards,
censored data, accelerated-life models, Kaplan-Meier estimator, stochastic
models, renewal processes, Bayesian methods for lifetime and reliability
data analysis.
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STAT 516: EXPERIMENTAL DESIGN (E)
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Prerequisite: STAT 500 or MATH 312 or 510, or
permission of instructor.
Co-requisite: Concurrent enrollment in STAT
598.
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Introduction
to the basic concepts in experimental design, analysis of variance,
multiple comparison tests, completely randomized design, general linear
model approach to ANOVA, randomized block designs, Latin square and related
designs, completely randomized factorial design with two or more
treatments, hierarchical designs, split-plot and confounded factorial
designs, and analysis of covariance.
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STAT 517: APPLIED TIME SERIES (O)
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Prerequisite: MATH 312 or 510, or permission
of instructor.
Co-requisite: Concurrent enrollment in STAT
598.
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The
basic time series models in both the time domain (ARMA models) and the
frequency domain (spectral models). The emphasis will be on application to
real data sets.
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STAT 518: NUMERICAL METHODS IN STATISTICS (SI)
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Prerequisites: MATH 351 and knowledge of a
programming language suitable for scientific computation, or permission of
instructor.
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Selected
topics in linear algebra and related numerical algorithms of special importance
in statistics: linear least squares, eigenvalues and eigenvectors, QR
decomposition, singular value decomposition, generalized inverses.
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STAT 519: INTRODUCTION TO MATHEMATICAL
STATISTICS (Y)
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Prerequisite: MATH 312 or 510, or permission of
instructor.
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Fundamentals
of statistical distribution theory, moments, transformations of random
variables, point estimation, hypothesis testing, confidence regions.
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STAT 520: DESIGN AND ANALYSIS OF SAMPLE SURVEYS
(E)
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Prerequisite: STAT 500 or STAT 110 or STAT 112
or MATH 312, or permission of instructor.
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Discussion
of the main designs and estimation techniques used in sample surveys:
simple random sampling, stratification, cluster sampling, double sampling, post-stratification,
ratio estimation. Nonresponse problems and measurement errors will also be
discussed. Many properties of sample surveys will be developed through
simulation procedures. The SUDAAN software package for analyzing sample
surveys will be used. This course may not be used for graduate degrees in
the Department of Statistics.
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STAT 531: CLINICAL TRIALS METHODOLOGY (Y)
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Prerequisite: A basic statistics course (Math
312/510) or STAT 500, or permission of instructor.
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Experimental
designs for randomized clinical trials, sources of bias in clinical
studies, informed consent and other ethical issues, logistics, interim
monitoring procedures (group sequential and Bayesian methods).
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STAT 540: ACTUARIAL STATISTICS (SI)
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Prerequisite: MATH 312 or 510, or permission
of instructor.
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The
course will cover the main topics required by students preparing for the
examinations in Actuarial Statistics, set by the Society of Actuaries. Such
topics include: life tables, life insurance and annuities, survival
distributions, net premiums and premium reserves, multiple life functions
and decrement models, valuation of pension plans, insurance models,
benefits and dividends.
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STAT 541: ACTUARIAL RISK THEORY (SI)
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Prerequisite: MATH 311 or APMA 310 or
permission of the instructor.
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In this
course, the basics for actuarial risk theory are developed. It begins with
the economics of insurance, and, using utility theory, shows why a risk
averse individual would purchase insurance. Insurance models are presented
and applied to calculate the probability of ruin, as a function cash
reserves, the portfolio of policies, etc. Both individual risk theory
(classical) and collective (modern) risk theory are fully discussed. The
necessary probabilistic and statistical tools are developed within the
course. The material covered is that required for the Society of Actuaries
(SOA) Exam 151: Actuarial Risk Theory.
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STAT 598: APPLIED STATISTICS LABORATORY (S)
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Co-requisite: Concurrent enrollment in a
500-level STAT applied statistics course.
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This
course, the laboratory component of the Department's applied statistics
program, deals with the use of computer packages in data analysis. Enrollment
in STAT 598 is required for all students in the Department's 500-level
applied statistics courses (STAT 512, 513, 514, 516, 517). STAT 598 may be
taken repeatedly provided that a student is enrolled in at least one of
these 500-level applied courses. However, no more than one unit of STAT 598
may be taken in any semester.
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STAT 711: FOUNDATIONS OF STATISTICS (Y)
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Prerequisite: STAT 519, or permission of
instructor.
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Introduction
to the concepts of statistics via the establishment of fundamental
principles which are then applied to practical problems. Such statistical
principles as those of sufficiency, ancillarity, conditionality, and
likelihood will be discussed.
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STAT 712: STATISTICAL INFERENCE (E)
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Prerequisite: STAT 711, or permission of
instructor.
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A
rigorous mathematical development of the principles of statistics. The
course covers point and interval estimation, hypothesis testing, asymptotic
theory, Bayesian statistics, and decision theory from a unified
perspective.
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STAT 713: GENERALIZED LINEAR MODELS (Y)
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Prerequisites: STAT 512 and STAT 519, or
permission of instructor.
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The
origins of generalized linear models, classical linear models, probit analysis,
logit models for proportions, log-linear models for counts, inverse
polynomial models, binary data, polytomous data, quasi-likelihood models,
and models for survival data.
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STAT 714: MULTIVARIATE STATISTICAL ANALYSIS (O)
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Prerequisites: STAT 513 and STAT 519, or
permission of instructor.
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Multivariate
normal distributions, maximum likelihood inference, invariance theory,
sample correlation coefficients Hotelling's T2 statistic, Wishart
distributions, discriminant analysis, MANOVA.
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STAT 715: NONPARAMETRIC STATISTICAL ANALYSIS
(E)
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Prerequisites: STAT 519 and one of STAT 512,
513, 514, 516, 517, or permission of instructor.
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Order
statistics, distribution-free statistics, U-statistics, rank tests and
estimates, asymptotic efficiency, Bahadur efficiency, M-estimates, one- and
two-way layouts, multivariate location models, rank correlation, linear
models.
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STAT 718: SAMPLE SURVEYS (O)
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Prerequisites:
MATH 312 or 510,
or permission of instructor.
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An
introduction to the design and analysis of sample surveys. Topics include
simple random sampling, stratified sampling, multistage (cluster) sampling,
double sampling, ratio and regression estimates. Theoretical discussions
are supplemented by computer simulated surveys, and studies of the
documentation of ongoing government sample surveys.
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STAT 719: STATISTICAL COMPUTING (SI)
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Prerequisites: STAT 512 and STAT 518, or
permission of instructor.
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Computational
methods for multiple linear regression, unconstrained optimization and
nonlinear regression, and model fitting based upon Lp norms and other
criteria, robust estimation.
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STAT 720: ADVANCED PROBABILITY THEORY FOR
APPLIED SCIENTISTS (Y)
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Prerequisites: MATH 531, or permission of
instructor.
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The
course will emphasize those techniques which are important for the applied
statistician: various forms of convergence for random variables, central
limit theorems, asymptotics for a transformation of a sequence of random
variables, and an introduction to martingales.
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STAT 721: ADVANCED LINEAR MODELS (O)
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Prerequisites: MATH 351, STAT 512, STAT 513,
STAT 519, or permission of instructor.
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Review of
matrix theory (various types of generalized inverses and their properties).
Theory and analysis of fixed effects linear models. Estimation of variance
components in random and mixed effects linear models. Various methods of
estimation of variance components such as: Henderson's three methods, MLE,
RMLE, MINQUE (and its modifications). Theory and analysis of random and
mixed effects models.
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STAT 731: ADVANCED DATA ANALYSIS (O)
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Prerequisite:
STAT 512, STAT
513, STAT 301/501 and HES 704, or permission of instructor.
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Modern
computer-intensive methods of data analysis, including splines and other
methods of nonparametric regression, bootstrap, techniques for handling
missing values and data reduction, nonlinear regression, graphical
techniques, penalized maximum likelihood estimation.
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STAT 812: TOPICS IN STATISTICS (SI)
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A study
of topics in statistics that are currently the subject of active research.
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STAT 817: ADVANCED TIME SERIES (SI)
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Prerequisites:
MATH 736, STAT 517,
or permission of instructor.
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An
introduction to stationary stochastic processes, related limit theorems and
spectral representations. Asymptotic theory for estimation in both the time
and frequency domains are covered. (OPTION A)
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STAT 831: ADVANCED SURVIVAL ANALYSIS (O)
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Prerequisite: STAT 514, STAT 519, STAT 720 and
STAT 731; or permission of instructor. STAT 720 may be replaced by MATH
736. MATH 511 is also recommended, but is not required.
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Martingale
theory and the counting process approach to survival analysis, asymptotic
theory of the Cox and related models, censoring, competing risks, multiple
events per subject, parametric survival models, advanced model diagnostics
for the Cox model, time-dependent covariates, bootstrap model validation,
frailty models.
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STAT 832: TOPICS IN BIOSTATISTICS (SI)
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A study
of topics in biostatistics that are currently the subject of active
research.
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STAT 912: STATISTICS SEMINAR (Y)
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Advanced
graduate seminar. Offerings in each semester are determined by student and
faculty interests.
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STAT 995: STATISTICAL CONSULTING (Y)
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Prerequisites: Current registration in the Statistics graduate
program, or permission of instructor.
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Introduction
to the practice of statistical consultation. The course will be taught by a
combination of formal lectures, meetings with clients of the statistical
consulting service, and sessions in the statistical computing laboratory.
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STAT 996: DIRECTED READING (Y)
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Research
into current statistical problems under faculty supervision.
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STAT 997: NON-TOPICAL RESEARCH, PREPARATION FOR
DOCTORAL RESEARCH (Y)
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For
doctoral research, taken before a dissertation director has been selected.
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STAT 999: NON-TOPICAL RESEARCH (Y)
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For
doctoral research, taken under the supervision of a dissertation director.
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Statistics Courses at UVa