Understanding row and column space

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Homework Help Overview

The discussion revolves around understanding the concepts of row and column space in linear algebra, particularly in relation to matrices. The original poster expresses difficulty in visualizing these concepts and seeks clarification on their meanings and dimensions.

Discussion Character

  • Conceptual clarification, Exploratory

Approaches and Questions Raised

  • Participants explore the definitions of row and column space through examples of matrices, discussing linear combinations of vectors. Questions about the dimensions of these spaces and the rank of the matrix are raised.

Discussion Status

Some participants provide concrete examples to illustrate the concepts, while others inquire about visual representations of row and column spaces. The discussion is ongoing, with various interpretations being explored.

Contextual Notes

There is a focus on understanding the relationship between the dimensions of row and column spaces and the rank of the matrix. The original poster's request for simplification indicates a need for foundational clarity.

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Understading row and column space

Homework Statement



I am having hard time trying to understand row and column space. Can anyone simplify the meanings of them so that i can visualize them well.

Homework Equations



dimension of row space = rank ? How? Why?

The Attempt at a Solution



Understanding other vectors
 
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Let's look at a concrete example. Suppose A is a 2 x 3 matrix, shown here:
[1 3 0]
[2 5 1]

Each of the two rows can be considered to be a vector in R^3, and each of the three columns can be considered to be a vector in R^2.

The row space of this matrix is the set of all linear combinations of the row vectors, or
c_1(1, 3, 0) + c_2(2, 5, 1).

Similarly, the column space is the set of all linear combinations of the column vectors, or
d_1(1, 2)^T + d_2(3, 5)^T + d_3(0, 1)^T.

For this matrix, what is the dimension of the row space? the column space? What is the rank of this matrix?

Now suppose that A is an m x n matrix, meaning it has m rows and n columns. Each of the m rows can be considered a vector with n components (because there are n columns). Each of the n columns can be considered a vector with m components. Just as in the first example, the row space of this matrix is the set of all linear combinations or the row vectors, and the column space of this matrix is the set of all linear combinations or the column vectors.
 
Understading row and column space

Thanks

on visualizing them in the graph or say pictorially, how would they look?
 


The two row vectors are a basis for a plane in R^3. The three column vectors span R^2 but aren't a basis -- there are too many vectors for a basis.
 

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