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STAT 256: Neural Computation
3.00 Credits
University of Vermont
Introduction to artificial neural networks, their computational capabilities and limitations, and the algorithms used to train them. Statistical capacity, convergence theorems, backpropagation, reinforcement learning, generalization. Prerequisites: Math 124 (or 271), Stat 153 or equivalent, computer programming. Cross-listing: CS 256/CSYS 256. Credits: 3
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STAT 261: Statistical Theory I
3.00 Credits
University of Vermont
Point and interval estimation, hypothesis testing, and decision theory. Application of general statistical principles to areas such as nonparametric tests, sequential analysis, and linear models. Prerequisites: STAT 251 or either STAT 151 or STAT 153 with instructor permission. Credits: 3
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STAT 261 - Statistical Theory I
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STAT 262: Statistical Theory II
3.00 Credits
University of Vermont
Point and interval estimation, hypothesis testing, and decision theory. Application of general statistical principles to areas such as nonparametric tests, sequential analysis, and linear models. Prerequisites: 241 with instructor permission or 261. Credits: 3
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STAT 262 - Statistical Theory II
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STAT 265: Integrated Product Development
3.00 Credits
University of Vermont
Project-based course focusing on the entire product life cycle. Team dynamics, process and product design, quality, materials, management, and environmentally-conscious manufacturing. Prerequisite: Senior standing. Credits: 3
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STAT 270: Stochastic Processes in EE
3.00 Credits
University of Vermont
Probability theory, random variables, and stochastic processes. Response of linear systems to random inputs. Applications in electrical engineering. Cross-listed with EE 270. Prerequisites: EE 171 and STAT 151. Credits: 3
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STAT 270 - Stochastic Processes in EE
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STAT 271: Filtering of Time Series
3.00 Credits
University of Vermont
Foundations of linear and nonlinear least squares estimation, smoothing and prediction, computational aspects, Kalman filtering, nonlinear filtering, parameter identification, and adaptive filtering. Cross-listed with EE 271. Prerequisite: EE 270. Credits: 3
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STAT 271 - Filtering of Time Series
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STAT 281: Statistics Practicum
1.00 - 4.00 Credits
University of Vermont
Intensive experience in carrying out a complete statistical analysis for a research project in substantive area with close consultation with a project investigator. Prerequisites: Any one of 200, 201, 221 through 237; or 253; some statistical software experience. No credit for graduate students in Statistics or Biostatistics. Credits: 1 - 4
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STAT 281 - Statistics Practicum
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STAT 293: Undergrad Honors Thesis
1.00 - 8.00 Credits
University of Vermont
A program of reading, research, design, and analysis culminating in a written thesis and oral defense. Honors notation appears on transcript and Commencement Program. Contact Statistics Program Director for procedures. Credits: 1 - 8
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STAT 294: Undergrad Honors Thesis
1.00 - 8.00 Credits
University of Vermont
A program of reading, research, design, and analysis culminating in a written thesis and oral defense. Honors notation appears on transcript and Commencement Program. Contact Statistics Program Director for procedures. Credits: 1 - 8
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STAT 295: Special Topics
1.00 - 4.00 Credits
University of Vermont
For advanced students. Lectures, reports, and directed readings on advanced topics. Prerequisite: As listed in course schedule. Credits: 1 - 4
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