3.5 Subspaces of R^p

Readings

Try the Preview Activity and read   Chapter 3 Section 5 in Understanding Linear Algebra by David Austin.

 

A subspace of [latex]\mathbb{R}^p[/latex] is a subset of vectors [latex]H[/latex] such that any linear combination of vectors in [latex]H[/latex] is also in [latex]H[/latex]

 

Applying the subspace definition:

A basis of a subspace [latex]H \subset \mathbb{R}^p[/latex] is a set of vectors in [latex]H[/latex] that are linearly independent and span [latex]H[/latex]. Any two bases of a subspace contain the same number of vectors. This number is called the dimension of the subspace, and is written [latex]dim(H)[/latex]

 

Video

Overview:

 

Subspaces of [latex]\mathbb{R}^p[/latex]

If A is an mxn matrix then, we can think of a matrix transformation [latex]T: \mathbb{R}^n \to \mathbb{R}^m[/latex], with [latex]T(\vec{x}) = A\vec{x}[/latex].

The Null space of A, Nul(A) is a subspace of the domain, [latex]\mathbb{R}^n. Nul(A) = \{\vec{x}| A\vec{x} =\vec{0}.\}[/latex]

 

Finding Nullspaces Example:

The Column space of A, Col(A) is a subspace of the codomain, [latex]\mathbb{R}^m[/latex]. It is the range of the matrix transformation T. [latex]Col(A) = \{\vec{y}| A\vec{x} =\vec{y}, \mbox{for some} \vec{x}\in \mathbb{R}^n \}[/latex]

Finding Column Spaces Example:

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Math 220, Matrices Copyright © 2018 by Kristen Pueschel is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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