I don't understand the rank of a matrix

  • Thread starter Thread starter mr_coffee
  • Start date Start date
  • Tags Tags
    Matrix rank
AI Thread Summary
The rank of a matrix is defined as the number of linearly independent rows or columns. To determine the rank, perform Gaussian elimination on the matrix and count the number of non-zero rows in the resulting matrix. For example, the rank of the first matrix provided is 3, indicating that all three columns are linearly independent. The rank reflects the maximum number of linearly independent vectors in the matrix, which is crucial for understanding its properties. Understanding the rank helps in analyzing the relationships between the vectors represented by the matrix.
mr_coffee
Messages
1,613
Reaction score
1
Hello everyone, can someone explain to me what the rank of a matrix is?
I have the following:
2 3 -2
2 6 0
-4 0 0
Rank = 3;

0 2 0 0
0 0 0 -4
0 0 0 0
9 0 0 0
rank = 3;


1 2
6 -3
Rank = 2;

I don't get it! any help would be great!
 
Physics news on Phys.org
Hey,

The rank of a matrix is the number of linearly independent rows in the matrix.

You can find the rank by performing Gaussian elimination. The rank will then be the number of non-zero rows in the resulting matrix.
 
To compute the rank of a matrix, do the following.

1) Let A be a m\times n matrix.
2) Perform gaussian-elimination on A
3) Count the number of non zero columns. This number is the rank of the matrix.

We'll start with your first example.
1) A = \left[ \begin{array}{ccc}2 & 3 & -2 \\2 & 6 & 0 \\-4 & 0 & 0 \\\end{array}\right]

2) Perform the gaussian-elimination on A
A' = \left[ \begin{array}{ccc}1 & 0 & 0 \\0 & 1 & 0 \\0 & 0 & 1 \\\end{array}\right]

3) Now we count the number of non-zero columns:
A' = \left[ \begin{array}{ccc}(1) & 0 & 0 \\0 & (1) & 0 \\0 & 0 & (1) \\\end{array}\right]

Rank = 3

----
Now, what does the rank mean? Well the rank of a matrix let's you know the number of columns that cannot be written as a linear combination of each other.

If you consider A' to be a matrix of vectors, we would have the following column vectors.

\vec{V_1} = (1,0,0)
\vec{V_2} = (0,1,0)
\vec{V_3} = (0,0,1)

These vectors are ALL linearly independent of each other. Which means that the column vectors in A are all linearly independent of each other.
 
Just don't forget that the rank only tells you the number of independent columns. If you are trying to find the spanning set, you must go back to the ORIGINAL matrix.
 
Awesome! thanks a lot guys! good explanation! :biggrin:
 
I multiplied the values first without the error limit. Got 19.38. rounded it off to 2 significant figures since the given data has 2 significant figures. So = 19. For error I used the above formula. It comes out about 1.48. Now my question is. Should I write the answer as 19±1.5 (rounding 1.48 to 2 significant figures) OR should I write it as 19±1. So in short, should the error have same number of significant figures as the mean value or should it have the same number of decimal places as...
Thread 'Collision of a bullet on a rod-string system: query'
In this question, I have a question. I am NOT trying to solve it, but it is just a conceptual question. Consider the point on the rod, which connects the string and the rod. My question: just before and after the collision, is ANGULAR momentum CONSERVED about this point? Lets call the point which connects the string and rod as P. Why am I asking this? : it is clear from the scenario that the point of concern, which connects the string and the rod, moves in a circular path due to the string...
Thread 'A cylinder connected to a hanging mass'
Let's declare that for the cylinder, mass = M = 10 kg Radius = R = 4 m For the wall and the floor, Friction coeff = ##\mu## = 0.5 For the hanging mass, mass = m = 11 kg First, we divide the force according to their respective plane (x and y thing, correct me if I'm wrong) and according to which, cylinder or the hanging mass, they're working on. Force on the hanging mass $$mg - T = ma$$ Force(Cylinder) on y $$N_f + f_w - Mg = 0$$ Force(Cylinder) on x $$T + f_f - N_w = Ma$$ There's also...
Back
Top