Courses
Statistics (FSBM)
0403. Introduction to
Biostatistics (3 s.h.)
Topics cover methods and concepts of Statistics 402, with special
emphasis on applications in health and biological sciences.
May be used to satisfy M.B.A. and M.S. requirement for Stat.
402.
0500. Quantitative Methods
for Business (3 s.h.)
This course is designed to introduce you to contemporary elementary applied statistics and to provide you with an appreciation for the uses of statistics in business, economics, everyday life, as well as hands-on capabilities needed in your later coursework and professional employment.
0501. Probability and
Statistics Theory I. (3 s.h.)
Prerequisite: calculus.
Topics include basic probability theory and combinatorial problems,
generating functions, random variables, probability distributions,
law of large numbers, and limit theorems.
0502. Probability and
Statistics Theory II (3 s.h.)
Prerequisite: Stat. 501
A comprehensive development of the theory of statistics, including
standard distributions, sampling distributions, general theory
of estimation, testing of hypotheses, statistical decision
theory, order statistics, linear statistical estimation.
0503. Statistical Methods
I. (3 s.h.)
Prerequisite: Stat. 402 or permission of instructor.
Introduction to frequently used methods. Includes probability,
estimation, tests of hypothesis, survey sampling, linear regression
data analysis, statistical computer packages.
0504. Statistical Methods
II. (3 s.h.)
Prerequisite: Stat. 503.
Introduction to multiple regression, analysis of variance,design
of experiments, robust techniques, analysis of covariance,
nonparametric analysis, and multivariate analysis. Statistical
packages such as SAS and MINITAB are used.
0509. Introduction to
Stochastic Models (3 s.h.)
Applicants of probability and simple stochastic processes,
including Markov Chains and Poisson processes, to problems
such as queueing, inventory, and reliability.
0510. Measure Theory
and Probability (3 s.h.)
Prerequisite: advanced calculus.
Introduction to measure theory, probability theory, Lebesque
integral, conditional probability.
0511. Sampling Theory (3
s.h.)
Prerequisite: Stat. 503 or permission of instructor.
Theory and application of sampling from finite populations.Topics
include random, stratified, cluster, and systematic sampling;
estimation of means and variances; optimal allocation of resources;
problems of nonsampling errors; and ratio and regression estimation.
0515. Matrix Theory for
Statistics (3 s.h.)
Prerequisite: undergraduate linear algebra
or permission of instructor.
Vector spaces; linear independence of vectors and basis; matrices
and algebraic operations on matrices; determinants; rank of
a matrix; inverse of nonsingular matrices; linear equations
and their solutions; generalized inverse of a matrix; eigen
values and vectors of matrices; diagonalization theorems; quadratic
forms and their reduction to sum of squares; Jacobians.
0518. Time Series Analysis
I. (3 s.h.)
Prerequisite: Stat. 502 or permission of instructor.
Theory and application of time series models illustrated with
forecasting problems. Considers spectrum analysis, autocorrelation
analysis, stationary and nonstationary linear processes, ARMA
and ARIMA models, seasonal time series and related materials.
0521. Linear Models I. (3
s.h.)
Prerequisite: Stat. 502 and Stat. 515 or permission
of instructor..
Theory and analysis of the overparameterized and cell means
forms of the linear statistical model that underlies designed
experiments. Emphasis on the "messy data" situations having
disproportionate cell sizes, empty cells and disconnectedness.
Use of SAS-GLM software to analyze about 10 real data sets.
0522. Design of Experiments
I. (3 s.h.)
Prerequisite: Stat. 504 or permission of instructor.
Principles of experimental designs, completely randomized designs,
multiple comparisons, randomized block design, latin square
design, missing value problems, analysis of covariance, and
factorial experiments.
0531. Applied Linear
Regression (3 s.h.)
Prerequisite: Stat. 504.
Simple linear regression. Multiple regression. Weighted least
squares, generalized least squares. Polynomial regression.
Dummy variables, comparing regression lines. Subset selection
procedures. Residual analysis, influentialobservations. Prediction.
0533. Applied Multivariate
Analysis I. (3 s.h.)
Prerequisite: Stat. 504, 515, or permission of instructor.
Multivariate normal distribution; marginal and conditional
distributions; estimation of population mean vector anddispersion
matrix; correlation, partial correlation, and multiple correlation
coefficients; Hotelling's T2; MANOVA; discriminant function;
repeated measurements analysis; principal components and canonical
correlation; factor analysis; and multidimensional scaling.
0550. Probability and
Statistics Theory for Business Applications (3
s.h.)
Prerequisite: calculus.
Topics covered: probability, density functions, moments, transformation
of variables, common distributions, estimation and tests of
hypothesis with emphasis on business applications.
0551. Regression, Time
Series, and Forecasting for Business Applications (3
s.h.)
Prerequisite: Stat. 402 or permission of instructor.
Application oriented. Standard statistical packages such as
SAS, MINITAB, or SPSS are introduced and extensively used in
the course. Topics include regression analysis, time series
analysis, and forecasting.
0552. Design of Experiments
I (3 s.h.)
0554. Survey Techniques
for Business Applications (3 s.h.)
Prerequisite: Stat. 402 or permission of instructor.
Application oriented. A course dealing with statistical and
nonstatistical aspects of organizing a sample survey. Included
are discussions of objectives, measurement, sample selection,
pilot testing, data collection, data editing, summarization
and interpretation of results in addition to describing the
various sampling schemes. Students may be required to plan
and execute a survey.
0555. Statistical Methods
for Business Research I (3 s.h.)
Prerequisite: Statistics 402, CIS 401, or equivalent.
Students must pass a placement examination to enter the
course..
Doctoral level, one-year sequence of courses for those students
in Business Administration program. Covers a variety of advanced
statistical methods useful in business research, including
the logistic regression, path analysis, factor analysis, discriminant
analysis, log-linear models, and clustering techniques. Emphasis
on rationales, assumptions, techniques, and interpretation
of results from computer packages. Relevant mathematical results
will be presented, but proofs or abstract arguments shall be
avoided. The students are required to work with SAS (or equivalent
packages) throughout the year. Experience in working with large
databases will be acquired through an arrangement of working
with each student's own field adviser.
0556. Statistical Methods
for Business Research II. (3 s.h.)
Prerequisite: Statistics 402, CIS 401, or equivalent.
Students must pass a placement examination to enter the
course..
Doctoral level, one-year sequence of courses for those students
in Business Administration program. Covers a variety of advanced
statistical methods useful in business research, including
the logistic regression, path analysis, factor analysis, discriminant
analysis, log-linear models, and clustering techniques. Emphasis
on rationales, assumptions, techniques, and interpretation
of results from computer packages. Relevant mathematical results
will be presented, but proofs or abstract arguments shall be
avoided. The students are required to work with SAS (or equivalent
packages) throughout the year. Experience in working with large
databases will be acquired through an arrangement of working
with each student's own field adviser.
0571. Nonparametric Methods (3
s.h.)
Prerequisite: Stat. 502 or permission of instructor.
A thorough course in nonparametric statistics. Estimation and
testing of hypothesis when the function form of the population
distribution function is not completely specified.
0572. Categorical Data
Analysis (3 s.h.)
Prerequisite: Stat. 502 or permission of instructor.
Sampling models for discrete data; Fisher's exact test; Gart's
test for residual effects; measures of association; log-linear
models; iterative proportion fitting; collapsing multidimensional
tables; conditional independence, and logistic regression.
0575. Clinical Trials (3
s.h.)
Prerequisite: Stat. 502 or permission of instructor.
Introduction to the special problems associated with medical
trials on humans. Topics include the debate concerning randomization,
use of historical data, ethics of experimentation, decision
theoretic approach to clinical trials, and applications of
sequential and adaptive sampling techniques. Discussion of
research articles.
0580. Pharmaceutical
Statistics I. (3 s.h.)
Prerequisite: Stat. 501-502, or equivalent.
Introduction to certain statistical problems associated with
pharmaceutical drug development. Topics include the bioequivalence
problems, population PK/PD modeling, and analysis of combination
drug trials. Research articles of current interest will be
discussed.
0585. Exploratory Data
Analysis I. (3 s.h.)
Prerequisite: Stat. 502 or 504 or permission ofinstructor.
Acquaints the student with applications of statistical theory.
Techniques and solutions for a broad spectrum of real-world
problems. Statistical computing emphasized.
0598. Independent Study (1-6
s.h.)
Prerequisite: approval of the department.
Special study in a particular aspect of statistics under thedirect
supervision of an appropriate graduate faculty member. No more
than six semester hours of independent study may be counted
toward degree requirements.
0599. Independent Study (1-6
s.h.)
Prerequisite: approval of the department.
Special study in a particular aspect of statistics under thedirect
supervision of an appropriate graduate faculty member. No more
than six semester hours of independent study may be counted
toward degree requirements.
0601. Advanced Statistical
Inference I. (3 s.h.)
Prerequisite: Stat. 502.
Random variables, inequalities, convergence types, Central
Limit Theorem, integration and expectation, conditional probability
and expectation, UMVU estimator, Bayes and Minimax estimators.
0602. Advanced Statistical
Inference II (3 s.h.)
Prerequisite: Stat. 601.
Hypothesis testing and confidence sets, Neyman-Pearson Lemma,
similar and unbiased tests, likelihood ratio tests.
0618. Time Series Analysis
II. (3 s.h.)
Prerequisite: Stat. 518 or permission of instructor.
Advanced topics on modern time series analysis from the time
domain and/or frequency domain perspective. Emphasis will be
placed on the analysis of multiple time series.
0621. Linear Models II. (3
s.h.)
Prerequisite: Stat. 521 or permission of instructor.
Continuation of Stat. 521, principally devoted to analysis
of mixed models and inference concerning variance components.
Topics covered include calculation of expected mean squares,
estimation by Henderson's Methods, ML, REML, MINQUE, MIVQUE.
Dispersion Mean Model. Computational algorithms and software.
0622. Design of Experiments
II. (3 s.h.)
Prerequisite: Stat. 522 or permission of instructor.
Covers symmetric and asymmetrical factorial experiments, fractional
replication, split plot design, balanced and partially balanced
incomplete block designs without and with recovery of interblock
information and lattice designs.
0633. Multivariate Analysis
II. (3 s.h.)
Prerequisite: Stat. 502 and 533 or permission
ofinstructor.
A study of specialized topics in multivariate analysis.
0662. Biometric Methods (3
s.h.)
Prerequisite: Stat. 502 or permission of instructor.
Presents the theory of biometry and explores its many applications.
Topics are taken from clinical trials, bioassay and survival
analysis. Topics discussed include the importance of randomization,
parallel assays, censored data, proportional hazard models,
and rank tests.
0701. Seminar in New
Topics in Statistics (3eachsemester
s.h.)
Prerequisite: permission of instructor.
Special topics in Statistics
0702. Seminar in New
Topics in Statistics (3eachsemester
s.h.)
Prerequisite: permission of instructor.
Special topics in Statistics
0799. Directed Study
in Statistics (variablecredit s.h.)
Prerequisite: departmental permission.
Preparation for preliminary examinations.
0800. Quantitative Business
Methods (3 s.h.)
Introduces descriptive statistical tools which are commonlyused
in business and decision making. Basic probability concepts
are covered and are employed using statistical inference methods.
Estimation, testing of hypotheses and applications. Statistical
package "Minitab" will be used as a tool for not only computations
but also for understanding statistical concepts. The course
will be rigorous in statistical concepts.
0802. Managerial Statistics (3
s.h.)
Prerequisite: Limited to students matriculated in
the Executive M.B.A. program.
Study advanced statistical techniques for managerial decision
making, including the theory and application of regression,
time series and forecasting, categorical data analysis, and
quality improvement techniques. Statistical packages, business
data sets, and case studies are used.
0896. Directed Study
in Statistics (variablecredit s.h.)
Prerequisite: departmental permission.
0899. Directed Study
in Statistics (variablecredit s.h.)
Prerequisite: departmental permission.
0999. Dissertation Research (1-12
s.h.)
Prerequisite: departmental approval.