Linear Algebra (Meaning of Rank)

In summary, the rank of an n x n matrix equals the number of linearly independent row vectors in the matrix. If there are more rows than columns in the matrix, then the rows are more linearly independent.
  • #1
DanielFaraday
87
0

Homework Statement



True or False:
If A is an n x n matrix, then the rank of A equals the number of linearly independent row vectors in A.

Homework Equations



None


The Attempt at a Solution



Okay, I know this is a ridiculously easy question, but I'm wondering if there is a catch to it. My inclination is to say this is true. But wouldn't this be true for ANY matrix? Why does the question limit it to an n x n matrix? Are they just being tricky?
 
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  • #2
DanielFaraday said:

Homework Statement



True or False:
If A is an n x n matrix, then the rank of A equals the number of linearly independent row vectors in A.

Homework Equations



None


The Attempt at a Solution



Okay, I know this is a ridiculously easy question, but I'm wondering if there is a catch to it. My inclination is to say this is true. But wouldn't this be true for ANY matrix? Why does the question limit it to an n x n matrix? Are they just being tricky?

Well, if it were n x m with n not equal to m, then the row rank and column rank would not generally be the same, right?

Also, if you have more rows than columns, what can you say about the linear independence of the rows...?

http://en.wikipedia.org/wiki/Rank_(linear_algebra )

.
 
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  • #3
berkeman said:
Well, if it were n x m with n not equal to m, then the row rank and column rank would not generally be the same, right?

Also, if you have more rows than columns, what can you say about the linear independence of the rows...?

http://en.wikipedia.org/wiki/Rank_(linear_algebra )

.

Thanks for your reply. In the wikipedia article that you cited (which I had read before posting this question) it says in the third sentence: "Since the column rank and the row rank are always equal, they are simply called the rank of A". I believe this statement is correct, which disagrees with your first point. Am I missing something?
 
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  • #4
DanielFaraday said:
Thanks for your reply. In the wikipedia article that you cited (which I had read before posting this question) it says in the third sentence: "Since the column rank and the row rank are always equal, they are simply called the rank of A". I believe this statement is correct, which disagrees with your first point. Am I missing something?

No, that sentence was my point. if n=m, then you use the term "rank" instead of differentiating between rows and columns. I think your original answer is correct, just that it cannot be extended always to cases where n is not equal to m. Hope I'm not just adding confusion here...
 
  • #5
Okay, that makes perfect sense. Thank you!
 

FAQ: Linear Algebra (Meaning of Rank)

What is the meaning of rank in linear algebra?

The rank of a matrix is the maximum number of linearly independent rows or columns in the matrix. In other words, it represents the number of independent equations or variables in the matrix. It is an important concept in linear algebra as it helps determine the dimension of the vector space spanned by the matrix.

How do you calculate the rank of a matrix?

The rank of a matrix can be calculated by performing row or column operations to reduce the matrix into its row echelon form or reduced row echelon form. The number of non-zero rows or columns in the reduced matrix will give the rank of the original matrix.

What is the significance of rank in linear algebra?

The rank of a matrix helps determine the number of independent equations or variables in a system, which is important in solving linear equations and understanding the properties of a system. It also helps determine the dimension of the vector space spanned by the matrix.

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 at most be equal to the smaller of the two. For example, a 3x4 matrix can have a maximum rank of 3.

How does the rank of a matrix affect its invertibility?

A square matrix is invertible if and only if its rank is equal to its number of rows (or columns). If the rank is less than the number of rows, the matrix is not invertible. The rank also helps determine the number of solutions to a system of linear equations, with a higher rank indicating a unique solution and a lower rank indicating infinitely many solutions or no solutions.

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