Definition

Let

If then we call row space of

If then we call column space of

If : Solution space of (which is subspace of ) then we call null space of

Interpretation

By definition of span, any linear combination of columns of is in the column space of . For example, if column vectors of , then .

ANY linear combination of columns of , is in the column space of .

And ANY linear combination of rows of , is in the row space of .

Finding basis of column/row space

Let : matrix

To find basis of :

  1. Obtain RREF of
  2. Find pivot column of

To find basis of :

  1. Obtain RREF of
  2. Find pivot column of

These pivot columns obtained from or form the basis for and respectively.

Example: Checking if a vector is in column space

Let

Then,

Suppose we have .

To check if , we have to check if there exists a solution such that the linear combination holds true.

Note

Basically, we’re trying to see if is in the span of column vectors of . Check the definitions.

So,

Using Gaussian Elimination, we end up with

On the fourth row of , we found that , which is a contradiction.

Thus, . Consequently, is not in the column space of .

Example: Finding basis of column/row space

Let

The RREF of and is:

According to row space,

Example: Finding null space

i.e., finding the solution space of :

Row reduce to RREF:

Columns 1 and 2 have pivots (basic variables x₁, x₂). Column 3 has no pivot (free variable x₃).

Set x₃ = 1:

  • x₁ - 1 = 0 → x₁ = 1
  • x₂ + 1 = 0 → x₂ = -1

Solution space: