Two proofs, with discussion, of the fact that an abstract linear transformation maps 0 to 0.
- Created On
- February 15th, 2017
- 7 years ago
- Views
- 2
- Type
- Handout
- Timeframe
- Pre-class
- Perspective
- Proof
- Language
- English
- Content Type
- text/html; charset=utf-8
Matrices can be thought of as transforming space, and understanding how this work is crucial for understanding many other ideas that follow in linear algebra...
- License
- Unlicense
- Created On
- May 25th, 2017
- 7 years ago
- Views
- 2
- Type
- Video
- Timeframe
- Pre-class
- Perspective
- Introduction
- Language
- English
- Content Type
- text/html; charset=utf-8
This is a guided discovery of the formula for Lagrange Interpolation, which lets you find the formula for a polynomial which passes through a given set of points.
- Created On
- June 8th, 2017
- 7 years ago
- Views
- 2
- Type
- Handout
- Perspective
- Application
- Language
- English
- Content Type
- text/html; charset=utf-8
Definition of the column space of a matrix; column space is a subspace; comparison to the null space; definition of a linear transformation between vector spaces; definition of kernel and range of a linear transformation
- Created On
- August 25th, 2017
- 7 years ago
- Views
- 3
- Type
- Video
- Language
- English
- Content Type
- text/html; charset=utf-8
Early in Chapter VS we prefaced the definition of a vector space with the comment that it was “one of the two most important definitions in the entire course.” Here comes the other. Any capsule summary of linear algebra would have to describe the subject as the interplay of linear transformations and vector spaces. Here we go.
- License
- GFDL-1.2
- Submitted At
- September 11th, 2017
- 7 years ago
- Views
- 3
- Type
- Textbook
- Language
- English
- Content Type
- text/html