Lectures (Video)
- 1. Linear Regression Background: Part 1
- 2. Linear Regression Background: Part 2
- 3. Linear Regression Derivation: Part 1
- 4. Linear Regression Derivation: Part 2
- 5. Linear Regression: Example
- 6. Linear Regression With Zero Intercept: Derivation
- 7. Linear Regression With Zero Intercept: Example
- 8. Power Model: Derivation: Part 1
- 9. Power Model: Derivation: Part 2
- 10. Power Model Transformed Data: Derivation
- 11. Power Model Transformed Data: Example Part 1
- 12. Power Model Transformed Data: Example Part 2
- 13. Exponential Model Regression Derivation: Part 1
- 14. Exponential Model Regression Derivation: Part 2
- 15. Exponential Model: Example Part 1
- 16. Exponential Model: Example Part 2
- 17. Exponential Model Transformed Data: Derivation
- 18. Exponential Model Transformed Data: Example Part 1
- 19. Exponential Model Transformed Data: Example Part 2
- 20. Saturation Growth Model Transformed Data: Derivation
- 21. Harmonic Decline Curve Transformed Data: Derivation
- 22. Harmonic Decline Curve Transformed Data: Example Part 1
- 23. Harmonic Decline Curve Transformed Data: Example Part 2
- 24. Polynomial Model Regression: Derivation Part 1
- 25. Polynomial Model Regression: Derivation Part 2
- 26. Polynomial Model Regression: Example Part 1
- 27. Polynomial Model Regression: Example Part 2
Numerical Methods V
Course Summary
This course is based on Numerical Methods - Regression made available by Holistic Numerical Methods Institute, University of South Florida under the Creative Commons BY-NC-SA license.
This is a course on the basics of numerical methods and how they are used to solve scientific and engineering problems. It is accompanied by a comprehensive set of video lectures, presentation slides, textbook notes, worksheets and application examples. The lectures are in short segments of less than 10 minutes. Part V covers regression analysis using linear regression model and nonlinear regression models.
Reading Material
1. Numerical Methods with Applications - Chapter 6Author: Autar Kaw et al.
Publisher: http://www.autarkaw.com
Published: May 4, 2010
ISBN: 978-0-578-05765-1
Course Material
1. A Primer on Statistical Terminology for Regression Analysis2. Introduction to Regression
3. Test Your Knowledge on Background of Regression
4. Physical Problem
Finding a regression model for calculating the contraction of a trunnion immersed in liquid nitrogen.
5. Comparing Nonlinear Regression Models - With and Without Data Linearization
6. On Adequacy of Regression Models
7. Multivariate Least Squares Fitting
8. Examples of Linear Regression
Civil Engineering
Computer Engineering
Industrial Engineering
Mechanical Engineering
9. Examples of Nonlinear Regression
Chemical Engineering
Computer Engineering
Electrical Engineering
10. Sample Tests
Linear Regression
Nonlinear Regression
