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2003-2004
College of Graduate Studies Bulletin |
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Course
Descriptions |
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Statistics
(STA)
Course
Schedules
STA
575 Introduction to Statistical Packages 3(3-0)
Introduction to statistical packages for data management and
data analysis. SPSS, SAS and S-PLUS are introduced.
Prerequisites: STA 282, STA 382 or permission of instructor.
STA 580 Applied Statistical
Methods I 3(3-0) D
Identical with BIS 580. Applications of statistical methods
including the usage of computer packages. Topics include
forecasting simple, and multiple regression, and analysis of
variance. Prerequisites: STA 282, STA 382.
STA 582 Experimental Designs
3(3-0)
Randomized block designs, Latin square designs, factorial
designs, fractional factorial designs, response surface
methods. Prerequisites: STA 580 or equivalent.
STA 583 Nonparametric
Statistics 3(3-0) D
Theory and applications of nonparametric methods. Topics
include one-, two-, and several sample problems, rank
correlation and regression, Kolmogorov-Simirnov tests and
contingency tables. Prerequisite: STA 382.
STA 584 Mathematical
Statistics I 3(3-0) D
Probability defined on finite and infinite samples spaces,
conditional probability and independence, random variables,
expectations, moment-generating functions, probability models,
limit theorems. Prerequisite: MTH 233.
STA 585 Mathematical
Statistics II 3(3-0) D
Introductory topics from mathematical theory of statistics:
population distributions, sampling distributions, point and
interval estimation, tests of hypotheses. Prerequisite: STA
584.
STA 586 Clinical Trials and
Survival Analysis 3(3-0)
Statistical simple and advanced techniques used in the
analysis and interpretation of clinical research data.
Emphasis on statistical techniques commonly used in chronic
disease analysis. Prerequisites: STA 382 or equivalent.
STA 587 Statistical Theory and
Methods for Quality Improvement 3(3-0)
Statistical theory and methods for optimizing quality and
minimizing costs: classical and recently developed on-line
methods and Taguchi's off-line quality and robust designs.
Prerequisites: STA 580.
STA 588 Sampling Techniques
3(3-0)
Principles of sampling; simple random sampling; stratified
random sampling; systematic sampling; cluster sampling; sample
size determination; ratio and regression estimates;
comparisons among the designs. Prerequisites: STA 382 or
equivalent.
STA
589 Times Series Forecasting 3(3-0)
Introduction to basis timer series forecasting techniques.
Topics include forecasting, Box-Jenkins models, time series
regression, exponential smoothing, and transfer function
models Prerequisites: STA 580, or permission of instructor.
STA 590 Applied Statistical
Methods II 3(3-0)
Multiway ANOVA, multiple comparison procedures, analysis of
covariance, repeated measures analysis, unbalanced data and
missing data analysis. Prerequisites: STA 580 and MTH 223.
STA
591 Statistical Methods for Data Mining 3(3-0)
Introduction to statistical techniques for data mining,
including an overview of data mining and its applications,
commonly used data mining techniques such as clustering,
classification, association and predictive modeling
techniques. Prerequisites: STA 580.
STA 596 Special Topics in
Statistics 1-6(Spec)
Subject matter not included in regular courses. May be taken
for credit more than once, total credit not to exceed six
hours. Prerequisites: Consent of the instructor.
STA 597 Independent Study
1-6(Spec)
Open to students with permission of instructor May be taken
for credit more than once, total credit not to exceed six
hours. Prerequisites: Consent of department chairperson and
instructor.
STA 680 Statistical Data
Analysis and Consulting 3(3-0)
Advanced data analysis techniques, including categorical data
analysis methods, logistic and loglinear models using
statistical software such as SAS, SPSS, and MINITAB.
Principles and techniques of statistical consulting.
Prerequisites: STA 590 or permission of instructor.
STA 682 Linear Models 3(3-0)
Theory and application of leas1t squares method and hypothesis
testing for the linear regression models. Prerequisites: MTH
525; STA 584.
STA 684 Theory of Statistical
Inference 3(3-0)
Stochastic convergence and limiting theorems, sampling
distributions, Theory of point estimation and hypothesis
testing, general linear hypotheses, sequential probability
ratio test. Prerequisites: MTH 532 and STA 584.
STA 686 Multivariate Analysis
3(3-0)
Multivariate normal distributions, multivariate methods
including multivariate analysis of variance, multivariate
regression, principal component analysis, factor analysis,
canonical correlation, discriminant analysis and cluster
analysis. Prerequisites: STA 580, 584.
STA 782 Generalized Linear
Models 3(3-0)
Theory and applications of generalized linear models, models
for continuous data, models for binary and polytomous data,
log-linear models, quasi-likelihood functions and model
checking. Prerequisites: STA 682.
STA 784 Theory of Estimation
3(3-0)
Theory of point estimation in Euclidean sample spaces. Topics
include unbiasedness, equivariance, global properties,
large-sample theory, and asymptotic optimality. Prerequisites:
STA 684; MTH 632.
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