Understanding row and column space

In summary, row and column space refer to the set of all linear combinations of the row and column vectors in a matrix. The dimension of the row space is equal to the rank of the matrix, and the column space is spanned by the column vectors. In a 2 x 3 matrix, the row space is a plane in R^3 and the column space is R^2. Visualizing them in a graph or pictorially, the row vectors form a basis for the plane, while the column vectors span R^2 but are not a basis.
  • #1
FourierX
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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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  • #2


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.
 
  • #3
Understading row and column space

Thanks

on visualizing them in the graph or say pictorially, how would they look?
 
  • #4


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.
 

Related to Understanding row and column space

What is row space?

Row space refers to the set of all possible linear combinations of the rows of a matrix. It represents the span of the rows and can be thought of as the "horizontal" space of the matrix.

What is column space?

Column space refers to the set of all possible linear combinations of the columns of a matrix. It represents the span of the columns and can be thought of as the "vertical" space of the matrix.

What is the relationship between row space and column space?

The row space and column space of a matrix are related by the fundamental property that the column space is the transpose of the row space. In other words, the column space of a matrix A is the row space of its transpose, AT.

Why is understanding row and column space important?

Understanding row and column space is important because it allows us to analyze the structure and properties of a matrix. It also helps us to solve systems of linear equations, find the rank of a matrix, and determine if a matrix is invertible.

How can we visualize row and column space?

We can visualize row and column space by plotting the rows or columns of a matrix as vectors in a coordinate system. The span of these vectors represents the row or column space, respectively. We can also use tools such as row and column reduction to simplify and visualize the space.

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