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Course Criteria
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3.00 Credits
Prerequisite: Introductory statistics course at or above the 2000 level or instructor permission. This course covers linear and multiple regression; one-and-two-way analysis of variance; chi-square and contingency tables; design, analysis, evaluation and interpretation of statistical models. Well-prepared students can skip STA 3024 and take either STA 4202 or 4203.
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3.00 Credits
Prerequisite: MAC 2312. This course will cover calculus-based probability, discrete and continuous random variables, joint distributions, sampling distributions, and the central limit theorem. Topics include descriptive statistics, interval estimates and hypothesis tests, ANOVA, correlation, simple and multiple regression, analysis of categorical data, and statistical quality control.
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3.00 Credits
will be used. Floating point arithmetic, numerical matrix analysis, multiple regression analysis, non-linear optimization, root finding, numerical integration, Monte Carlo sampling, survey of density estimation.
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3.00 Credits
will be used. A continuation of STA 4102 in computational techniques for linear and non-linear statistics. Statistical image understanding, elements of pattern theory, simulated annealing, Metropolis-Hastings algorithm, Gibbs sampling.
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3.00 Credits
Prerequisite: STA 2122, STA 2171, STA 3032, or QMB 3200. Subsequent credit for STA 5206 is not permitted. One and two-way classifications, nesting, blocking, multiple comparisons, incomplete designs, variance components, factorial designs, confounding.
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3.00 Credits
Prerequisite: STA 2122, STA 2171, STA 3032, STA 4322, or QMB 3200. Subsequent credit for STA 5207 is not permitted. General linear hypothesis, multiple correlation and regression, residual analysis, and model identification.
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3.00 Credits
Prerequisite: A statistics course above STA 1013 or instructor permission. Simple, stratified, systematic, and cluster random sampling. Ratio and regression estimation, multistage sampling.
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3.00 Credits
Prerequisite: MAC 2313. Distribution of random variables, conditional probability and independence, multivariate distributions, sampling distributions, Bayes' rule, counting problems, expectations. Credit not given for both STA 4321 and STA 4442.
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3.00 Credits
Prerequisites: STA 4321 and MAC 2313. Subsequent credit for STA 5325 is not permitted. Sufficiency, point estimation, confidence intervals, hypothesis testing, regression, linear models, Bayesian analysis.
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3.00 Credits
Prerequisite: MAC 2312. Subsequent credit for STA 5440 is not permitted. Random variables, probability distributions, independence, sums of random variables, generating functions, central limit theorem, laws of large numbers. Not open to Statistics majors or minors. Credit not given for both STA 4321 and STA 4442.
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