Rank of a 4x4 Matrix A: Linear Algebra Homework Solution

Click For Summary
SUMMARY

The rank of the matrix A, defined as the maximal number of linearly independent rows or columns, is determined to be 3. The row-reduced form of A is given as {[1 0 0 0], [0 1 0 -1/3], [0 0 1 0]}, indicating three linearly independent rows. The second and fourth columns are dependent, confirming that the rank cannot exceed 3. Therefore, the rank of matrix A is conclusively 3.

PREREQUISITES
  • Understanding of linear independence in vector spaces
  • Familiarity with row reduction techniques in linear algebra
  • Knowledge of matrix rank definitions and properties
  • Basic proficiency in manipulating matrices
NEXT STEPS
  • Study the concept of linear independence in greater depth
  • Learn advanced row reduction techniques for larger matrices
  • Explore the implications of rank in linear transformations
  • Investigate applications of matrix rank in solving systems of equations
USEFUL FOR

Students of linear algebra, educators teaching matrix theory, and anyone seeking to deepen their understanding of matrix rank and linear independence.

underacheiver
Messages
12
Reaction score
0

Homework Statement


Find the rank of A =
{[1 0 2 0]
[4 0 3 0]
[5 0 -1 0]
[2 -3 1 1]}

Homework Equations





The Attempt at a Solution


i row reduced A to be:
{[1 0 0 0]
[0 1 0 -1/3]
[0 0 1 0]}

where do i go from here?
 
Physics news on Phys.org
I think you omitted a last row of zeros. Ok, what does rank mean?
 
The column rank of a matrix A is the maximal number of linearly independent columns of A. Likewise, the row rank is the maximal number of linearly independent rows of A.

Since the column rank and the row rank are always equal, they are simply called the rank of A.
 
underacheiver said:
The column rank of a matrix A is the maximal number of linearly independent columns of A. Likewise, the row rank is the maximal number of linearly independent rows of A.

Since the column rank and the row rank are always equal, they are simply called the rank of A.

Good! So how many linearly independent rows are there? If you have no idea, quote the definition of linear independence.
 
so is it 3? because the 2nd and 4th columns are dependent.
 
underacheiver said:
so is it 3? because the 2nd and 4th columns are dependent.

Yes, the second and fourth columns being dependent means the rank is at most 3. Now you have to check that the three remaining vectors are linearly independent. It's easier to see this if you look at the row reduction.
 

Similar threads

Replies
5
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
9
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 7 ·
Replies
7
Views
1K
  • · Replies 5 ·
Replies
5
Views
1K