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STAT 474: Statistical Programming
3.00 Credits
University of Delaware
Introduction to statistical programming languages, possibly including SAS and R. PREREQ: STAT200 or STAT408 or MATH205.
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STAT 474 - Statistical Programming
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STAT 475: Environmental Statistics
3.00 Credits
University of Delaware
Introduction to statistical methods for analyzing environmental data. Relevant probability and sampling theory is introduced, as well as procedures for summarizing, modeling and estimating and making inferences from environmental data. A computer-based statistical package is used to explore behavior of different statistical techniques with a variety of environmental data sets. RESTRICTIONS: If STAT475 is taken, degree credit cannot be given for any of the following courses: STAT470, STAT471 or MATH450.
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STAT 566: SPECIAL PROBLEM
1.00 - 12.00 Credits
University of Delaware
No course description available.
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STAT 566 - SPECIAL PROBLEM
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STAT 567: SEMINAR
1.00 - 12.00 Credits
University of Delaware
No course description available.
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STAT 567 - SEMINAR
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STAT 601: Probability Theory for Operations Research and Statistics
3.00 Credits
University of Delaware
Provides the basic background in probability theory for further work in statistics and operations research. Basic topics: sample spaces and axioms of probability; conditional probability and independence; Bayes theorem; random variables; moments and moment generating functions; transformations of random variables; common families of distributions; multivariate distributions, covariance and correlation; probability inequalities and limit theorems. RESTRICTIONS: Students are expected to have had Analytic Geometry & Calculus C.
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STAT 601 - Probability Theory for Operations Research and Statistics
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STAT 602: Mathematical Statistics
3.00 Credits
University of Delaware
Derived sampling distributions; decision theory; estimation theory; multivariate normal; hypotheses testing; special topics. PREREQ: STAT601
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STAT 602 - Mathematical Statistics
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STAT 603: Statistical Computing and Optimization
3.00 Credits
University of Delaware
Many modern statistical machine learning problems for Big Data analytics can be formulated by function optimization and linear algebraic computation. This course will provide necessary knowledge of convex optimization and matrix computation, and gain fundamental understandings of important numerical algorithms commonly used in statistical machine learning. We will emphasize on both efficient implementation and understanding for statistical computing problems. The topics to be covered include: fundamental methods for matrix and linear systems computation, matrix decomposition, convex analysis, duality and KKT conditions, 1st/2nd order methods, EM methods. Important statistical computing applications including GLM, SVM, sparsity learning, greedy function approximation, and deep neural networks will be covered. PREREQ: STAT601 and STAT602. RESTRICTIONS: Basic programming knowledge (such as R, Python, MATLAB, or C/C++) is assumed.
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STAT 608: Statistical Research Methods
3.00 Credits
University of Delaware
An introductory statistics course for advanced undergraduate and graduate students with applications for life sciences, business, health, engineering, and the social sciences. The course managing and describing data; the normal, t, F and chi squared distributions; the logic of inference; inferential statistics for one and two sample problems; analysis of table data; analysis of variance; and multiple regression. The course is taught using statistical software.
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STAT 608 - Statistical Research Methods
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STAT 609: Regression and Experimental Design
3.00 Credits
University of Delaware
Introduction and overview of inferential methods used in analyzing regression models and linear models for experimental designs. PREREQ: STAT608 or equivalent
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STAT 611: Regression Analysis
3.00 Credits
University of Delaware
Simple linear and nonlinear regression. Subset regression; principal component and ridge regression. Introduction to experimental design and design models. RESTRICTIONS: Students are expected to have completed a Linear Algebra course.
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STAT 611 - Regression Analysis
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