|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
3.00 Credits
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
-
3.00 Credits
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
-
3.00 Credits
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
-
3.00 Credits
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
-
3.00 Credits
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
-
3.00 Credits
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
-
1.00 - 4.00 Credits
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
-
1.00 - 8.00 Credits
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
-
1.00 - 8.00 Credits
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
-
1.00 - 4.00 Credits
For advanced students. Lectures, reports, and directed readings on advanced topics. Prerequisite: As listed in course schedule. Credits: 1 - 4
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2025 AcademyOne, Inc.
|
|
|