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There is a growing need for qualified statistical analysts of the ever-increasing amounts of data collected in business, industry, and government. The Certificates in Applied Statistics program is designed to give students a strong background in statistical methodology and data analysis in preparation for opportunities in the work force or for graduate studies.

There is a growing need for qualified statistical analysts of the ever-increasing amounts of data collected in business, industry, and government. The Certificates in Applied Statistics program is designed to give students a strong background in statistical methodology and data analysis in preparation for opportunities in the work force or for graduate studies.

Students will gain
competence in such topics as descriptive statistics, estimation, confidence
intervals, probability and inferential techniques, simple and multiple
regression, analysis of variance, and more-advanced topics. Students can focus
on a particular application area such as economics, psychology, sociology,
geology or environmental science through the choice of an elective course and
the data analysis project.

Programs are offered
at the undergraduate and graduate level.

ONE COURSE IN
PROBABILITY:

·
MATH
3800 - Probability and Statistics for Engineers. Basic probability theory,
discrete and continuous random variables, point and interval estimation, test
of hypotheses, one-way analysis of variance, and simple linear regression.
Note: no co-credit with MATH 4810. Prereq: MATH 2411; coreq: MATH 2421.
Semester Hours: 3 to 3

or

·
MATH
4810 – Probability. Examines elementary
theory of probability, including independence, conditional probability, and
Bayes’ theorem; random variables, expectations and probability distributions;
joint and conditional distributions; functions of random variables; limit
theorems, including the central limit theorem. Note: No co-credit with MATH
3800. Prereq: MATH 3191; Coreq: MATH 2421. Cross-listed with MATH 5310.
Semester Hours: 3 to 3

It is strongly
advised that MATH4810 be taken rather than MATH3800.

ONE COURSE IN
MATHEMATICAL STATISTICS:

·
MATH 4820 – Statistics. Point and confidence
interval estimation, principles of maximum likelihood, sufficiency and
completeness, tests of simple and composite hypothesis, linear models and
multiple regression, analysis of variance. Prereq: MATH 3800 or MATH 4810
(preferred). Cross-listed with MATH 5320. Semester Hours: 3 to 3

ONE ADVANCED APPLICATIONS COURSE:

·
MATH 4387 - Regression Analysis, Modeling and Time
Series. Topics include linear and multiple regression, basic experimental
designs, one-way analysis of variance. Emphasis is on practical aspects and
applications of linear models to the analysis of data in business engineering,
behavioral, biological and physical sciences. Prereq: MATH 3191 and 3800/4820.
Cross-listed with MATH 5387. Semester Hours: 3 to 3 When Offered: FALL

ONE ELECTIVE:

·
Any
statistics course in the Department of Mathematical and Statistical Sciences at
the 4000 level or higher (*must be
pre-approved by the Certificate Coordinator*). MATH4830 cannot apply towards
the certificate.

·
ECON
4030 - Data Analysis with SAS

·
ECON
4150 - Economic Forecasting

·
ECON
4811 - Introduction to Econometrics

·
GEOG
4770 - Applied Statistics for the Natural Sciences

·
GEOL
4770 - Applied Statistics for the Natural Sciences

·
Equivalent
course pre-approved by the Certificate Coordinator

TWO FUNDAMENTAL
COURSES IN STATISTICS:

·
MATH 5320 – Statistics. Point and confidence
interval estimation, principles of maximum likelihood, sufficiency and
completeness, tests of simple and composite hypothesis, linear models and
multiple regression, analysis of variance. Prereq: MATH 3800. MATH 4810 highly
recommended, but not required. Cross-listed with MATH 4820. Semester Hours: 3
to 3. When Offered: SPRING

·
MATH 5387 - Regression Analysis, Modeling and Time
Series. Topics include linear and multiple regression, basic experimental
designs, one-way analysis of variance. Emphasis is on practical aspects and
applications of linear models to the analysis of data in business engineering
and behavioral, biological and physical sciences. Prereq: MATH 3191 and
3800/4820. Cross-listed with MATH 4387. Semester Hours: 3 to 3 When Offered:
FALL

ONE ADVANCED APPLICATIONS COURSE:

Topics vary from year to year. Course must be pre-approved by certificate
coordinator and cannot be MATH5830. Representative courses include:

·
MATH 5394 - Experimental Designs. Completely
randomized block designs, factorial and fractional factorial experiments,
balanced incomplete block designs, response surface methods. Prereq: MATH 4387/5387.
Cross-listed with MATH 4394. Semester Hours: 3 to 3.

·
MATH 6388 - Advanced Statistical Methods for
Research. The second in a two-semester course in applied statistics. Topics
include multifactor analysis of variance and covariance, categorical data,
general linear models, bootstrapping, and other computationally intensive
statistical methods. Prereq: MATH 5387. Semester Hours: 3 to 3.

·
MATH 6393 - Introduction to Bayesian Statistics.
Prior and posterior distributions, conjugate models, single and multiparameter
models, hierarchical models, mixture models, numerical methods for evaluating
posteriors, Monte Carlo methods, and Markov chain Monte Carlo. Prereq: MATH
3800 or both MATH 4810 and MATH 4820 (or equivalent). Some computer programming
experience. Semester Hours: 3 to 3.

ONE ELECTIVE:

·
Any
statistics course in the Department of Mathematical and Statistical Sciences at
the 5000 level or higher (*must be
pre-approved by the Certificate Coordinator*). MATH5830 cannot apply towards
the certificate.

·
ECON
5150, ECON 5813, ECON 5823

·
ENVS
5600

·
GEOG
5770

·
GEOL
5770

·
SOC
5183

·
Equivalent
course pre-approved by the Certificate Coordinator

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