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Course Criteria
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3.00 Credits
Topics include a study of auto-correlation and part i a l auto-correlation functions, multiplicative decomposition of a time series, construction and evolution of auto-regressive models, exponential smoothing procedures, classical regression analysis and Box-Jenkins methodology. Interpretation and computer analysis, using SAS or another appropriate package are emphasized. This course may be used to fulfill the writing application course requirement with additional prerequisites including STAT 4294 and departmental approval.
Corequisite:
A grade of C or better in MATH 3302 or STAT 3309
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3.00 Credits
Principles of design and analysis of experiments including randomized blocks, Latin, Greco-Latin and Youden squares, multiple comparisons and orthogonal contrasts. Introduction to factorial designs and split plots and use of computer statistical programs. This course may be used to fulfill the writing application course requirement with additional prerequisites including STAT 4294 and departmental approval.
Corequisite:
A grade of C or better in MATH 3302 or STAT 3310
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3.00 Credits
Basic t1 theory and structure of regression, with applications in business, simple linear regression, correlation, multiple linear and polynomial regression, R2 and adjusted R2, significance tests multicollinearity, comparison with ANOVA, dummy variables and coding, stepwise regression, prediction and inference in regression, analysis of covariance, interactions, time series, index numbers and forecasting. Emphasis on use of computer packages and interpretation of printouts. This course may be used to fulfill the writing application course requirement with additional prerequisites including STAT 4294 and departmental approval.
Corequisite:
A grade of C or better in MATH 3302 or STAT 3309
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3.00 Credits
Applications of the most useful tools of operations research. Topics are selected from linear programming, the simplex method, the dual, the transportation model, networks, integer and dynamic programming and other topics.
Corequisite:
A grade of C or better in MATH 1305 and STAT 3309, or MATH 2307
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3.00 Credits
Intensive study under the guidance of a member of the Computer and Mathematical Sciences faculty culminating in an individually researched and formally written report and oral presentation dealing with the applications of the statistical sciences in the studentās area of specialization and related to one type of business or industry in the Houston area. Cross-listed as CS 4395, MATH 4395. Credit may not be earned for more than one.
Corequisite:
COMM 1304, ENG 3302, grade of B or better in STAT 4294, 3.0 GPA, senior standing and departmental approval
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3.00 Credits
This course will focus on core computational techniques which are useful for statistical research and advanced applications. We will be interested in developing skills and knowledge useful in the development of modern statistical procedures. Topics include a brief overview of traditional numerical analysis techniques; a discussion of optimization and root finding methods useful for estimation and a discussion of Numerical and Monte Carlo integration which is useful for statistical influence. We will also use the UHD cluster for high performance computing.
Corequisite:
B or higher in STAT 3309, or MATH 3302, or departmental approval
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