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Course Criteria
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3.00 Credits
(3-0) 3 hours credit. Prerequisites: EE 3423 and either EGR 2323 or MAT 3253. Probability, random variables, distribution and density functions, limit theorems, random processes, correlation functions, power spectra, and response of linear systems to random inputs.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: MAT 2213. Elementary probability, random variables, binomial, Poisson, normal and exponential distributions, elementary queuing theory, sampling distributions, point and interval estimation, hypothesis tests, principles of experimentation.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 3003, STA 3513, STA 3533, or STA 3543. Introduction to methods for analyzing discrete (categorical) data. Course emphasizes the uses and interpretations of the methods rather than the underlying theory. Topics include Two-way and Three-Way Contingency Tables, Partial Association, Cochran-Mantel-Haenszel Method, Generalized Linear models, Model Inference and Model Checking, Logistic Regression, Loglinear Models, and Models for Matched Pairs.
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3.00 Credits
No course description available.
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3.00 Credits
No course description available.
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3.00 Credits
No course description available.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: STA 3513. Probability models, Poisson processes, finite Markov chains, including transition probabilities, classification of states, limit theorems, queuing theory, and birth and death processes.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3003, STA 3533, or STA 3543. An introduction to regression analysis, with emphasis on practical aspects, fitting a straight line, examination of residuals, matrix treatment of regression analysis, fitting and evaluation of general linear models, and nonlinear regression.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: One of the following: MS 3313, PSY 3013, STA 1993, STA 2303, STA 3003, STA 3533, or STA 3543. General concepts in the design and analysis of experiments. Emphasis will be placed on both the experimental designs and analysis and tests of the validity of assumptions. Topics covered include completely randomized designs, randomized block designs, complete factorials, fractional factorials, and covariance analysis. The use of computer software packages will be stressed.
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3.00 Credits
No course description available.
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