| STATISTICS
(ST) |
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| ST 150 |
Contemporary
Mathematics |
1 cr |
|
This
course gives an overview of modern mathematics and
statistics from the point of view of the practitioners.
The course is designed for majors in mathematics
and statistics at all levels as well as those students
who are considering mathematics and statistics as
a major or minor area of study. Topics usually included
are elements of geometry, algebra, analysis, methods
of statistical inference, the role of the computer
in the analytical sciences; these topics vary from
semester to semester. This course cannot be taken
for credit simultaneously with MA 150, but may be
repeated in different semesters. |
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| NOTE:
May be offered for Honors Credit. |
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| ST
210 |
Statistical
Reasoning and Applications (C) |
3
cr |
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|
An introduction to modern statistics designed
to provide the student with a solid foundation
in statistical concepts, reasoning and applications.
Emphasis given to problem identification, methodology
selection and interpretation of results. Analysis
of data accomplished by extensive use of statistical
computer software, thereby minimizing manual
computation. Coverage includes descriptive statistics,
probability models, estimation, hypothesis testing,
design of experiments and analysis of variance
(ANOVA), linear regression and correlation.
Prerequisite: High School level algebra is recommended.
Computer Lab fee.
|
| |
| NOTE: ST 210
is intended for students in all disciplines except
Engineering, Computer Science, and Mathematics.
|
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| NOTE: May be
offered for Honors Credit. |
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| ST
310 |
Statistical
Research Techniques |
3
cr |
|
| Continuation
of ST 210 providing a more rigorous treatment
of methodologies introduced in ST 210. Additional
coverage will be given to experimental design,
analysis of variance (ANOVA), regression, model
building, nonparametric techniques, contingency
table analysis, sampling and survey methods, and
statistical simulations. Statistical computer
software will be extensively used for data analysis.
Prerequisite: ST 210. Computer Lab fee. |
| |
| NOTE: Credit
for only ONE course from ST 310, ST 315 and ST
320 is allowed. |
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| ST
315 |
Applied
Probability and Statistics |
3
cr |
|
| Concepts
of probability theory, discrete and continuous
probability distributions including gamma, beta,
exponential and Weibull, descriptive statistics,
sampling, estimation, confidence intervals, testing
of hypothesis, ANOVA and multiple comparisons,
linear and multiple regression, correlation, nonparametric
analysis, contingency table analysis, computer-assisted
data analysis using appropriate statistical software.
Prerequisite: MA 125. Computer Lab fee. |
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| NOTE:
ST 315 and ST 320 are intended for students in
Engineering, Computer Science, and Mathematics.
ST 315 covers additional probability distributions
while ST 320 additionally covers concepts of quality
control and acceptance sampling. Students in these
disciplines should consult with their academic
advisor for appropriate choice between ST 315
and ST 320. Credit for only ONE course from ST
310, ST 315 and ST 320 is allowed. |
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| ST
320 |
Applied
Statistical Analysis |
4
cr |
|
| Descriptive
statistics, probability distributions, sampling,
estimation, confidence intervals and hypothesis
testing, experimental designs, ANOVA and multiple
comparisons, linear and multiple regression, correlation,
nonparametric analysis, goodness of fit, contingency
table analysis, quality control, acceptance sampling,
computer-assisted data analysis using appropriate
statistical software. Prerequisite: MA 125. Computer
Lab fee. |
| |
| NOTE:
ST 315 and ST 320 are intended for students in
Engineering, Computer Science, and Mathematics.
ST 315 covers additional probability distributions
while ST 320 additionally covers concepts of quality
control and acceptance sampling. Students in these
disciplines should consult with their academic
advisor for appropriate choice between ST 315
and ST 320. |
| |
| NOTE:
Credit for only ONE course from ST 310, ST 315
and ST 320 is allowed. |
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| ST
335 |
Applied
Regression Analysis |
3
cr |
|
| Simple,
polynomial and multiple linear regression; residual
and lack-of-fit analysis; simple, multiple, partial
and multiple-partial correlation analysis; model
building algorithms, dummy variables; analysis
of covariance; model comparisons; analysis of
experimental designs including messy data; nonlinear
regression models; computer-assisted data analysis
using appropriate statistical software. Prerequisite:
ST 210 or 315 or 320. Computer Lab fee. |
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|
ST 340
|
Design
and Analysis of Experiments |
3
cr |
|
| Principles,
constructions, and analysis of experimental designs
to include completely randomized, randomized complete
block, latin square and split plot designs, factorial
experiments, designs with nested and/or crossed
factors, multifactor experiments with randomization
restrictions, transformations, incomplete block
designs, multiple comparisons including contrasts,
confounding, fractional replication, computer-assisted
data analysis. Prerequisite: ST 210 or 315 or
320. Computer Lab fee. |
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| ST
345 |
Sampling
and Survey Techniques |
3
cr |
|
Sampling
concepts and designs for survey investigations;
sampling methodologies including applications of
simple random, stratified, one-and two-stage cluster,
and systematic sampling; sample size determination;
ratio and regression estimation; population size
estimation; random response modeling; acceptance
sampling including applications of single and multiple
2-class attribute sampling plans; computer-assisted
data analysis using appropriate statistical software.
Prerequisite: ST 210 or 315 or 320. Computer Lab
fee. |
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| ST
350 |
Applied
Time Series Analysis |
3
cr |
|
| Fundamentals
concepts; classical regression models as forecasting
models, exponential smoothings, stationary and
nonstationary models, additive and multiplicative
decompositions, moving average, autoregressive,
ARMA and ARIMA processes, estimation in MA, AR,
ARMA and ARIMA processes. Box-Jenkins methodology,
computer aided modeling, applications. Prerequisite:
ST 310 or 315 or 320 or 335. Computer Lab fee. |
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| ST
355 |
Nonparametric
Statistical Methods |
3
cr |
|
| Distribution-free
analysis of location and scale measures, non-parametric
treatment of fundamental statistical designs,
nonparametric comparison procedures, association
and contingency table analysis, nonparametric
goodness-of-fit procedures, and tests for randomness,
nonparametric regression and other measures of
association, computer intensive statistical methods.
Prerequisite: ST 210 or 315 or 320. Computer Lab
fee. |
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| ST
415 |
Statistical
Quality Control and Reliability |
3 cr |
|
| Probability
distributions in quality control, inferences about
process quality, control charts for attributes
and variables, process capability analysis, economic
design of control charts, cusum charts, acceptance
sampling by attributes and variables, reliability
concepts, censoring, definitions and properties
of survival distributions, methods of estimating
and comparing reliability distributions, Kaplan-Meier
estimation, burn-in models with a major emphasis
on computer-assisted data analysis. Prerequisite:
Any 300 level ST course. Computer Lab fee. |
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| ST
425 |
Applied
Linear Models |
3
cr |
|
| Some
results of matrix algebra, multivariate normal
distributions, distributions of quadratic forms,
general linear models, design models with one
factor and two factors including interaction,
component-of-variance models, computing techniques.
Prerequisite: MA 237 and ST 335 or 340. Computer
Lab fee. |
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| ST
450 |
Categorical
Data Analysis |
3
cr |
|
| Analysis
of two-way, three-way and higher dimensional contingency
tables using log-linear models, measures of association
for nominal and ordinal tables, multiple-factor
models, multiple response models, logistic regression,
weighted least squares. Prerequisite: Any 300
level ST course. Computer Lab fee. |
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| ST
460 |
Multivariate
Statistical Analysis |
3
cr |
|
| Multivariate
normal distribution, sampling distribution, hypothesis
testing, principal components and introduction
to factor analysis, canonical correlation analysis,
discriminant and classification analysis, MANOVA.
Prerequisite: Any 300 level ST course. Computer
Lab fee. |
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| ST
470 |
Theory
of Statistics |
3
cr |
|
| A
comprehensive introduction to the mathematical
foundations of statistics. Sufficient statistics
and information. Parameter estimation, maximum
likelihood and moment estimation, optimality properties
of estimators and confidence intervals. Hypothesis
testing, likelihood ratio tests and power functions.
Credit for both ST 470 and MA 551 is not allowed.
Prerequisite: MA 451 or MA 550. |
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| ST
480 |
Statistical
Practicum (W) |
1
cr |
|
| Relates
to the student's classroom studies with actual
statistical problems encountered in practice.
Working with the departmental statistical consultant,
the student will participate in providing statistical
assistance to research faculty in applied fields.
Prerequisite: Approval of department chair. Computer
Lab fee. |
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| ST
490 |
Special
Topics |
1-3
cr |
|
| Selected
topics in advanced undergraduate applied statistics.
This course may be repeated for a maximum of six
credits. |
|
| ST
494 |
Directed
Studies |
1-3
cr |
|
Directed
study. May be repeated for a
maximum of six credits. Prerequisite: Permission
of the department chair. |
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| ST
499 |
Honors
Senior Project |
3-6
cr |
|
| With
the guidance and advice of a faculty mentor, Honors
Students will identify, and carry out a research
project in Statistics. The outcome of the research
project will include a formal presentation at
the annual Honors Student Colloquium. The senior
project will be judged and graded by three members
of the faculty, chaired by the faculty mentor. |
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| ST
540 |
Statistics
in Research I |
3
cr |
|
| A
service course for graduate students in disciplines
other than mathematics and statistics. A non-calculus
exposition in support of application. Coverage
includes descriptive statistics, probability and
probability distributions, sampling, estimation,
tests of significance, analysis of variance, correlation,
linear, polynomial, and multiple linear regression
including residual and lack of fit analysis, nonparametric
procedures, contingency table analysis, and computer
assisted data analysis using appropriate computer
software. Computer Lab fee. |
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| ST
545 |
Statistics
in Research II |
3
cr |
|
| Continuation
of ST 540. Coverage includes regression analysis
through matrices, multiple, partial and multiple-partial
correlation analysis, model building algorithms,
non-linear regression, analysis of covariance,
completely randomized, randomized complete block,
and factorial experimentation for equal and unequal
cell replication, logistic regression, resampling,
basic multivariate techniques, and computer assisted
data analysis. Prerequisite: ST 540. Computer
Lab fee. |
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| ST
550 |
Environmental
Statistics |
3
cr |
|
| Sampling
environmental populations, parametric and nonparametric
estimation; applications of lognormal, Weibull,
gamma and beta distributions; locating hot spots;
censored data; outlier detection; trend analysis,
seasonality; estimation of animal abundance. Prerequisite:
ST 540. Computer Lab fee. |
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College
of Arts and Sciences
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