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STAT 609: Or Stat&Non Para Meth
3.00 Credits
Texas A & M University-Galveston
Order Statistics and Non-Parametric Methods. (3-0). Credit 3. Application of distribution-free and rank procedures for estimation, confidence intervals construction and hypotheses testing; both exact and approximate methods considered. Prerequisite: STAT 601, 641 or 652.
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STAT 609 - Or Stat&Non Para Meth
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STAT 610: Distribution Theory
3.00 Credits
Texas A & M University-Galveston
Theory of Statistics - Distribution Theory. (3-0). Credit 3. Brief introduction to probability theory; distributions and expectations of random variables, transformations of random variables and order statistics; generating functions and basic limit concepts. Prerequisite: MATH 409 or concurrent enrollment in MATH 409.
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STAT 610 - Distribution Theory
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STAT 611: Theory Of Inference
3.00 Credits
Texas A & M University-Galveston
Theory of Statistics - Inference. (3-0). Credit 3. Theory of estimation and hypothesis testing; point estimation, interval estimation, sufficient statistics, decision theory, most powerful tests, likelihood ratio tests, chi-square tests. Prerequisite: STAT 610 or equivalent.
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STAT 611 - Theory Of Inference
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STAT 612: Thry Of Linear Models
3.00 Credits
Texas A & M University-Galveston
Theory of Linear Models. (3-0). Credit 3. Matrix algebra for statisticians; Gauss-Markov theorem; estimability; estimation subject to linear restrictions; multivariate normal distribution; distribution of quadratic forms; inferences for linear models; theory of multiple regression and AOV; random-and mixed-effects models. Prerequisite: Course in linear algebra.
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STAT 612 - Thry Of Linear Models
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STAT 613: Stat Methodology I
3.00 Credits
Texas A & M University-Galveston
Statistical Methodology I. (3-0). Credit 3. Elements of likelihood inference; exponential family models; group transformation models; survival data; missing data; estimation and hypotheses testing; nonlinear regression models; conditional and marginal inferences; complex models-Markov chains, Markov random fields, time series, and point processes. Prerequisite: STAT 612.
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STAT 613 - Stat Methodology I
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STAT 614: Probability For Stat
3.00 Credits
Texas A & M University-Galveston
Probability for Statistics. (3-0). Credit 3. Probability and measures; expectation and integrals, Kolmogorov's extension theorem; Fubini's theorem; inequalities; uniform integrability; conditional expectation; laws of large numbers; central limit theorems Prerequisite: STAT 610 or its equivalent.
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STAT 614 - Probability For Stat
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STAT 615: Stochastic Processes
3.00 Credits
Texas A & M University-Galveston
Stochastic Processes. (3-0). Credit 3. Survey of the theory of Poisson processes, discrete and continuous time Markov chains, renewal processes, birth and death processes, diffusion processes and covariance stationary processes. Prerequisites: STAT 611; MATH 409.
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STAT 615 - Stochastic Processes
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STAT 616: Mutivariate Analysis
3.00 Credits
Texas A & M University-Galveston
Multivariate Analysis. (3-0). Credit 3. Multivariate normal distributions and multivariate generalizations of classical test criteria, Hotelling's T2, discriminant analysis and elements of factor and canonical analysis. Prerequisites: STAT 611 and 612.
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STAT 616 - Mutivariate Analysis
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STAT 618: Stat Mach Learn & Mining
3.00 Credits
Texas A & M University-Galveston
Statistical Aspects of Machine Learning and Data Mining. (3-0). Credit 3. This course will examine the statistical aspects of techniques used to examine data streams which are large scale, dynamic, and heterogeneous. This course will examine the underlying statistical properties of classification; trees; bagging and boosting methods; neural networks; support vector machines; cluster analysis; and independent component analysis. Prerequisites: STAT 610, 611, and 613.
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STAT 618 - Stat Mach Learn & Mining
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STAT 620: Asymptotic Statistics
3.00 Credits
Texas A & M University-Galveston
Asymptotic Statistics. (3-0). Credit 3. Review of basic concepts and important convergence theorems; elements of decision theory; delta method; Bahadur representation theorem; asymptotic distribution of MLE and the LRT statistics; asymptotic efficiency; limit theory for U-statistics and differential statistical functionals with illustrations from M-,L-,R-estimation; multiple testing. Prerequisite: STAT 614.
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STAT 620 - Asymptotic Statistics
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