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Course Criteria
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3.00 Credits
No course description available.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: MAT 1223. Fundamental concepts of probability and statistics with practical applications to engineering problems. Emphasis on sampling, statistical inference, measurement error analysis and quantifying risk, safety and reliability in engineering design.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: Completion or concurrent enrollment in MAT 1153, MAT 1203, MAT 1214, or an equivalent. Data collection and experimental design; numeric and graphical displays of data; basic probability, Bayes' Theorem, random variables, statistical concepts and models; tests of means and variances of two or more populations; simple simulations and inferences based on resampling; introduction to statistical computation packages and the development of writing, presentation, and evaluation skills.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: STA 1993, STA 3003, STA 3513, or an equivalent. Linear algebra preliminaries, the multivariate normal distribution, tests on means, discriminant analysis, cluster analysis, principal components, and factor analysis. Use of software packages will be emphasized. Open to students of all disciplines.
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3.00 Credits
(3-0) 3 hours credit. Prerequisite: MS 1023, PSY 3013, STA 1043, STA 1053, STA 2303, STA 3003, STA 3533, or STA 3543 Research techniques for collecting quantitative data: sample surveys, designed experiments, simulations, and observational studies; development of survey and experimental protocols; measuring and controlling sources of measurement error.
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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 3513, STA 3533, STA 3543, or equivalent. Tests of location, goodness-of-fit tests, rank tests, tests based on nominal and ordinal data for both related and independent samples, and measures of association.
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3.00 Credits
(3-0) 3 hours credit. Prerequisites: MAT 1223 and STA 3003. Discrete and continuous distributions, moments and generating functions, bivariate and multivariate distributions and their applications. Functions of random variables, sampling distributions and the Central Limit Theorem.
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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 or an equivalent. Confidence intervals, hypothesis testing, maximum likelihood estimation, moment estimators, Bayes' estimates, linear and general linear models, including multiple regression and ANOVA.
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