Determining the rank of a matrix

In summary, the OP attempted to solve a homework problem that involved columns and rows being considered as separate entities, but was unable to do so because of the linear dependence between them.
  • #1
influx
164
2

Homework Statement


2136c8.png


Homework Equations


N/A

The Attempt at a Solution


I know that they got a rank of 2 since there are 2 linearly independent columns but what if we decided to count rows? In that case we would have 4 linearly independent rows which would suggest the rank is 4? How do we reconcile between these?
 
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  • #2
You should try to prove the linear independence of the four rows. Or simply draw them in a plane.
 
  • #3
influx said:

Homework Statement


2136c8.png


Homework Equations


N/A

The Attempt at a Solution


I know that they got a rank of 2 since there are 2 linearly independent columns but what if we decided to count rows? In that case we would have 4 linearly independent rows which would suggest the rank is 4? How do we reconcile between these?

No. Just because you have 4 rows does not mean you have 4 independent rows. In fact, you can have at most 2 independent vectors of dimension 2!

In fact, you can see that Row_3 = 2*Row_2 - Row_1 and Row_4 = - Row_1 - 4*Row_2..

REMEMBER: in any matrix, the number of linearly-independent rows equals the number of linearly-independent columns. That is an important basic theorem of linear algebra.
 
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  • #4
fresh_42 said:
You should try to prove the linear independence of the four rows. Or simply draw them in a plane.

I hope you mean linear dependence.
 
  • #5
Ray Vickson said:
I hope you mean linear dependence.
No, I meant linear independency. My goal was to let the OP see by himself why this won't be possible and learn out of it.
 
  • #6
fresh_42 said:
No, I meant linear independency. My goal was to let the OP see by himself why this won't be possible and learn out of it.

OK: I found the wording confusing.
 
  • #7
Ray Vickson said:
OK: I found the wording confusing.
He claimed the rows to be linear independent, so to ask for a proof seemed to be logic. Thus he would have learned multiple things: don't claim, what you cannot prove, the calculations with linear dependencies and linear independencies are basically the same, and a (failed) proof would have simultaneously shown two free parameters solving the dimension formula. All within this tiny example.
 

1. What is the rank of a matrix?

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

2. How is the rank of a matrix determined?

The rank of a matrix is determined by performing row operations to reduce the matrix to its row echelon form, and then counting the number of non-zero rows.

3. Can the rank of a matrix be greater than the number of rows or columns?

No, the rank of a matrix cannot be greater than the number of rows or columns. It can be at most equal to the smaller of the two.

4. What does a matrix with full rank mean?

A matrix with full rank means that all of its rows and columns are linearly independent, and therefore it has the maximum possible rank.

5. Why is determining the rank of a matrix important?

The rank of a matrix is important in various applications of linear algebra, such as solving systems of linear equations and finding the inverse of a matrix. It also provides information about the dimension of the vector space spanned by the rows or columns of the matrix.

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