Department of Statistics
Kerchof Hall
University of Virginia
P.O. Box 400135
Charlottesville, VA 229044135
(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, one halftime,
and seven adjunct appointments. The halftime faculty has a joint appointment
in the department of mathematics, and the 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.
Interdisciplinary Major in Applied Statistics The Interdisciplinary
Major in Applied Statistics provides students with the opportunity to integrate
the study of statistics with another quantitatively intensive discipline. Knowledge
of statistics is becoming increasingly important in many disciplines, so that
students completing this major will have many options available upon graduation.
Students completing this major will be well prepared to design
experimental studies and analyze data, in both their emphasis field and other
areas. They will also be well prepared for graduate study in statistics, and
with a modest amount of advance planning will be able to complete an MS in Statistics
at UVa with one additional year of study. Students interested in the 5year
B.A./M.S. program should contact the Department’s major advisor.
The major program has four tracks: Biostatistics, Econometrics,
Engineering Statistics, and Mathematical Statistics. The prerequisite for all
tracks: Single variable calculus through the second semester, fulfilled by one
of Math 122, Math 132, APMA 111.
Track 1: Biostatistics
The Biostatistics track is suitable for students using it as a primary major
or a second major in conjunction with a major in Biology. Courses required for
this track are:
 BIOL 201202 Introduction to Biology
 One 300level or higher course in Biology
 One of the following:
STAT 311 Applied Statistics and Probability
MATH 310312 ProbabilityStatistics
APMA 311 Applied Statistics and Probability
APMA 310312 ProbabilityStatistics
 Four additional courses (plus associated onecredit STAT 598 labs) from
among the following:
STAT 512 Applied Linear Models
STAT 513 Applied Multivariate Statistics
STAT 514 Survival Analysis and Reliability Theory
STAT 516 Experimental Design
STAT 517 Applied Time Series
STAT 518 Numerical Methods in Statistics
STAT 519 Introduction to Mathematical Statistics
STAT 525 Longitudinal Data Analysis
STAT 526 Categorical Data Analysis
STAT 531 Clinical Trials
Track 2: Econometrics
The Econometrics track is suitable for students as a primary major, or will
serve well as a second major for students in Economics or Commerce. Courses
required for this track are:
 ECON 201202 Principles of Economics: MicroeconomicsMacroeconomics
 One of the following:
STAT 311 Applied Statistics and Probability
MATH 310312 ProbabilityStatistics
APMA 311 Applied Statistics and Probability
APMA 310312 ProbabilityStatistics
 Five additional courses (plus associated onecredit STAT 598 labs) from
among the following:
ECON 372 Introductory Econometrics
ECON 471 Economic Forecasting
STAT 512 Applied Linear Models
STAT 513 Applied Multivariate Statistics
STAT 514 Survival Analysis and Reliability Theory
STAT 516 Experimental Design
STAT 517 Applied Time Series
STAT 518 Numerical Methods in Statistics
STAT 519 Introduction to Mathematical Statistics
STAT 525 Longitudinal Data Analysis
STAT 526 Categorical Data Analysis
Track 3: Engineering Statistics
The engineering statistics track is designed for SEAS students
who want to have a second major in the College. However, it is also be possible
for a College student to opt for this track. Courses required for this track
are:
 One of the following:
APMA 310312 ProbabilityStatistics
APMA 311 Applied Statistics and Probability
STAT 311 Applied Statistics and Probability
MATH 310312 ProbabilityStatistics
 Two of the following:
APMA 308 Linear Algebra or MATH 351 Linear Algebra
SYS 334 System Evaluation
SYS 360 Probability Models for Economic and Business Analyses
SYS 421 Data Analysis
 Courses to bring the total to eight (not including associated onecredit
STAT 598 labs) from among the following:
ECON 372 Introductory Econometrics
STAT 512 Applied Linear Models
STAT 513 Applied Multivariate Statistics
STAT 514 Survival Analysis and Reliability Theory
STAT 516 Experimental Design
STAT 517 Applied Time Series
STAT 518 Numerical Methods in Statistics
STAT 519 Introduction to Mathematical Statistics
STAT 525 Longitudinal Data Analysis
STAT 526 Categorical Data Analysis
Track 4: Mathematical Statistics
The target audience for this track are College students who
would like an applied quantitative major. Courses required for this track are:
 Math 310 Introduction to Mathematical Probability
 One of the following:
STAT 311 Applied Statistics and Probability
MATH 312 Statistics
APMA 311 Applied Statistics and Probability
APMA 312 Statistics.
 One of the following:
MATH 351 Linear Algebra
APMA 308 Linear Algebra
 At least five additional courses (plus associated onecredit STAT 598
labs) from among the following:
Math 511 Stochastic Processes
STAT 512 Applied Linear Models
STAT 513 Applied Multivariate Statistics
STAT 514 Survival Analysis and Reliability Theory
STAT 516 Experimental Design
STAT 517 Applied Time Series
STAT 518 Numerical Methods in Statistics
STAT 519 Introduction to Mathematical Statistics
STAT 525 Longitudinal Data Analysis
STAT 526 Categorical Data Analysis
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
the Department of Statistics, 131 Kerchof Hall, P.O. Box 400135, Charlottesville,
Virginia 229044135; (434) 9243222; www.stat.virginia.edu.
Course Descriptions
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 PC or a UNIX system, 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, 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 PC
or a UNIX system, 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.
