Department of Statistics
P.O. Box 400135
University of Virginia
Charlottesville, VA 229044135
Phone: (434) 9243222 Fax: (434) 9243076
www.stat.virginia.edu
Overview Statistics is a means of analyzing data
to gain insight into real problems. It is focused on problem solving,
rather than on methods that may be useful in specific settings.
Statistics is unique in its ability to quantify uncertainty. Thus
statistics has become a crucial tool in all aspects of modern society,
providing insight in such fields as public policy, law, medicine,
the social sciences, and the natural sciences.
The Department of Statistics shares the newly emerged consensus
among statisticians that statistical education should focus on data
analysis and statistical reasoning rather than the presentation
of a coterie of methods. As importantly, the department believes
that the mathematical tools underlying statistical inference are
significant and necessary for statistics education, but those tools
must necessarily remain secondary in the training of statisticians.
Because of these views, the statistics program strongly emphasizes
its consulting service, which provides statistical consultation
to all branches of the University. Through this service, statistics
students gain valuable insight into all branches of the field while
acquiring practical training in problem solving.
The Department of Statistics offers a broad range of courses covering
all areas of applied and theoretical statistics.
Faculty The faculty consist of six fulltime,
two halftime, and three adjunct appointments. The halftime faculty
have primary appointments in the department of mathematics, and
the three adjunct faculty have primary appointments in the departments
of biostatistics, economics, and systems engineering. This collection
of disciplines, in addition to the interests of the fulltime faculty,
ensures that the department is able to cater to the interests of
diverse students.
Students Students who graduate with indepth
training in statistics enjoy a large range of opportunities. Some
pursue employment in the public or private sector, working as actuaries,
consultants, data analysts, or teachers, among many fields. Others
do graduate study in fields such as economics, finance, mathematics,
operations research, psychology, and, of course, statistics.
Minor in Statistics and Data Analysis The minor
in statistics and data analysis is designed to meet the needs of
several types of students: the student interested in applying statistics
to some other field, the student interested in exploring a future
career in biostatistics or applied statistics, the student interested
in a career in actuarial statistics, or the mathematically minded
student interested in graduate study in statistics.
Requirements for Minor in Statistics and Data Analysis
Five (5) courses selected from: all STAT courses numbered 300 or
above, MATH 312 and 511. These five courses must include STAT 512
and, at most, one of MATH 312 or STAT 500.
With consent of the statistics faculty, a student who has had an
appropriate introductory statistics course in another department
may be exempted from the MATH 312/STAT 500 requirement. Such a student
still needs to take five courses from among MATH 511 and all STAT
courses numbered 300 or above.
Courses used to satisfy the minor in statistics and data analysis
cannot be used to satisfy the requirements of another major. For
example, a student who takes MATH 310/312 to satisfy the requirements
of the major in mathematics, must take five additional courses from
MATH 511 and the STAT courses numbered 300 or above (excluding STAT
500).
Sample Programs The following are examples of
programs for a student intending to pursue the minor in statistics
and data analysis:
 A general program in applied statistics: STAT 500, 512, 513,
516, 313.
 A general program in biostatistics: STAT 500, 512, 531, 514,
301.
 An actuarial preparatory program: MATH 312; STAT 512, 519, 540,
541.
 A program for graduate study in statistics: MATH 312, 511; STAT
512, 513, 519. MATH 351 and 531 are also recommended.
 Students should be aware that, except for MATH 312, 511; STAT
500, 512, 513, and 519, all courses for the minor in statistics
and data analysis are offered in alternate years. Please consult
the department's Web site for the offering schedule.
Additional Information For more information contact
Daniel Keenan, Graduate and Undergraduate Advisor, Department of
Statistics, 109 Halsey Hall, Charlottesville, Virginia 22903; (434)
9243048; Fax: (434) 9243076; www.stat.virginia.edu.

Note The entering College student is
encouraged to take the introductory course, STAT 110. This course,
entitled Chance, is intended to make students aware of the ubiquity
and importance of basic statistics in public policy and everyday
life. The course uses a casestudy approach based on current chance
events reported in daily newspapers and current scientific journals.
Credits earned in this course may be counted towards the College's
natural science area requirements. Students are also encouraged
to take mathematics courses which serve as prerequisites for higherlevel
statistics courses.
STAT 110  (3) (Y)
Chance: An Introduction to Statistics
Studies introductory statistics and probability, visual methods
for summarizing quantitative information, basic experimental design
and sampling methods, ethics and experimentation, causation, and
interpretation of statistical analyzes. Applications use data drawn
from current scientific and medical journals, newspaper articles,
and the Internet. Students will not receive credit for both STAT
110 and STAT 112.
STAT 112  (3) (S)
Introduction to Statistics
Includes graphical displays of data, relationships in data, design
of experiments, causation, random sampling, probability distributions,
inference, confidence intervals, tests of hypotheses, and regression
and correlation. Students will not receive credit for both STAT
110 and STAT 112.
STAT 212  (4) (S)
Introduction to Statistical Analysis
Prerequisite: MATH 121 or equivalent. Corequisite: Concurrent enrollment
in a discussion section of STAT 212.
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.
STAT 301  (3) (Y)
Statistical Computing and Graphics
Prerequisite: STAT 110 or 112 or instructor permission.
Introduces statistical computing using SPLUS. Topics include descriptive
statistics for continuous and categorical variables, methods for
handling missing data, basics of graphical perception, graphical
displays, exploratory data analysis, and the simultaneous display
of multiple variables. Students should be experienced with basic
textediting and file manipulation on either a PCor a UNIXsystem,
and with either a programming language (e.g. BASIC) or a spreadsheet
program (e.g. MINITAB or EXCEL). Credit earned in this course cannot
be applied toward a graduate degree in statistics.
STAT 313  (3) (O)
Design and Analysis of Sample Surveys
Prerequisite: STAT 110 or 112 or MATH 312, or instructor permission.
Discusses the main designs and estimation techniques used in sample
surveys; including simple random sampling, stratification, cluster
sampling, double sampling, poststratification, and ratio estimation.
Nonresponse problems and measurement errors are also discussed.
Many properties of sample surveys are developed through simulation
procedures. The SUDAAN software package for analyzing sample surveys
is used.
STAT 500  (3) (Y)
Introduction to Applied Statistics
Prerequisite: Instructor permission.
Introduces 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, chisquare, and F), and one and twosample inference,
power and sample size calculations, introduction to nonparametric
methods, oneway ANOVA and multiple comparisons. Students must also
enroll in STAT 598 for 1 credit.
STAT 501  (3) (Y)
Statistical Computing and Graphics
Prerequisite: STAT 110 or 112, and graduate standing or instructor
permission.
Students who have received credit for STAT 301 may not take STAT
501 for credit. Introduces statistical computing using SPLUS. Topics
include 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 textediting and file manipulation on either a PCor a UNIXsystem,
and with either a programming language (e.g. BASIC) or a spreadsheet
program (e.g. MINITAB or EXCEL). Credit earned in this course cannot
be applied toward a graduate degree in statistics.
STAT 512  (3) (Y)
Applied Linear Models
Prerequisite: MATH 312 or 510 or instructor permission; corequisite: STAT
598.
Topics include linear regression models, inferences in regression
analysis, model validation, selection of independent variables,
multicollinearity, influential observations, auto correlation in
time series data, polynomial regression, nonlinear regression, and
other topics in regression analysis.
STAT 513  (3) (O)
Applied Multivariate Statistics
Prerequisite: MATH 351 and 312 or 510 or instructor permission;
corequisite: STAT 598.
Topics include matrix algebra, random sampling, multivariate normal
distributions, multivariate regression, MANOVA, principal components,
factor analysis, discriminant analysis. Statistical software is
used.
STAT 514  (3) (Y)
Survival Analysis and Reliability Theory
Prerequisite: MATH 312 or 510, or instructor permission; corequisite: STAT
598.
Topics include lifetime distributions, hazard functions, competingrisks,
proportional hazards, censored data, acceleratedlife models, KaplanMeier
estimator, stochastic models, renewal processes, and Bayesian methods
for lifetime and reliability data analysis.
STAT 515  (3) (SI)
Actuarial Statistics
Prerequisite: MATH 312 or 510, or instructor permission.
Covers the main topics required by students preparing for the examinations
in Actuarial Statistics, set by the American Society of Actuaries.
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, and benefits and dividends.
STAT 516  (3) (E)
Experimental Design
Prerequisite: MATH 312 or 510, or instructor permission; corequisite: STAT
598.
Introduces the basic concepts in experimental design. Topics include
analysis of variance, multiple comparison tests, completely randomized
design, general linear model approach to analysis of variance, randomized
block designs, Latin square and related designs, completely randomized
factorial design with two or more treatments, hierarchical designs,
splitplot and confounded factorial designs, and analysis of covariance.
STAT 517  (3) (O)
Applied Time Series
Prerequisite: MATH 312 or 510, or instructor permission; corequisite: STAT
598. Studies the basic time series models in both the time domain
(ARMA models) and the frequency domain (spectral models). Emphasizes
application to real data sets.
STAT 518  (3) (SI)
Numerical Methods in Statistics
Prerequisite: MATH 351 and knowledge of a programming language suitable
for scientific computation, or instructor permission. Studies selected
topics in linear algebra and related numerical algorithms of special
importance in statistics, including linear leastsquares, eigenvalues
and eigenvectors, QR decomposition, singular value decomposition,
and generalized matrix inverses.
STAT 519  (3) (Y)
Introduction to Mathematical Statistics
Prerequisite: MATH 312 or 510, or instructor permission.
Studies the fundamentals of statistical distribution theory, moments,
transformations of random variables, point estimation, hypothesis
testing, confidence regions.
STAT 520  (3) (O)
Design and Analysis of Sample Surveys
Prerequisite: STAT 112 or MATH 312, and graduate standing or instructor
permission.
Discusses the main designs and estimation techniques used in sample
surveys, including simple random sampling, stratification, cluster
sampling, double sampling, poststratification, ratio estimation.
Nonresponse problems and measurement errors are also discussed.
Many properties of sample surveys are developed through simulation
procedures. The SUDAAN computer package for analyzing sample surveys
is used. Students who have received credit for STAT 313 may not
take STAT 520 for credit.
STAT 531  (3) (Y)
Clinical Trials Methodology
Prerequisite: A basic statistics course (MATH 312/510), or instructor
permission.
Studies experimental designs for randomized clinical trials, sources
of bias in clinical studies, informed consent, logistics, and interim
monitoring procedures (group sequential and Bayesian methods).
STAT 598  (1) (Y)
Applied Statistics Laboratory
Corequisite: A 500level STAT applied statistics course.
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 500level applied statistics courses (STAT 501,
512, 513, 514, 516, 517, 520). STAT 598 may be taken repeatedly
provided that a student is enrolled in at least one of these 500level
applied courses. However, no more than one unit of STAT 598 may
be taken in any semester.
STAT 599  (3) (IR)
Topics in Statistics
Prerequisite: Instructor permission.
Studies topics in statistics that are not part of the regular course
offerings.
