Linear Algebra and rank problem.

In summary: Eg. for A= [a_11,a_12;a_13; a_21; a_22; a_23] after row reducing we would have:A= [a_11,a_11;a_12,a_12;a_13,a_13; a_21,a_21;a_22,a_22;a_23,a_23]
  • #1
georgeh
68
0
I have the following problem which I can't figure out.

Let A = [a_11,a_12;a_13; a_21; a_22; a_23;]
Show that A has rank 2 if and only if one or more of the determinants

| a_11,_a_12; a_21,a_22| , |a_11,a_13;a_21,a_23|,|a_12,a_13;a_22,a_23|
I know its a 2x3 matrix..which the det. wouldn't apply since it is not square. Not sure how to proceede
 
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  • #2
You might start by stating the problem correctly

"Show that A has rank 2 if and only if one or more of the determinants
| a_11,_a_12; a_21,a_22| , |a_11,a_13;a_21,a_23|,|a_12,a_13;a_22,a_23|" is what?? What is supposed to be true about them?

"I know its a 2x3 matrix..which the det. wouldn't apply since it is not square."
That's irrelevant- the problem doesn't say anything about the determinant of A (which doesn't exist) only the determinants of those 2 by 2 subsets.
 
  • #3
HallsofIvy said:
You might start by stating the problem correctly

"Show that A has rank 2 if and only if one or more of the determinants
| a_11,_a_12; a_21,a_22| , |a_11,a_13;a_21,a_23|,|a_12,a_13;a_22,a_23|" is what?? What is supposed to be true about them?
the det is not equal to zero..
"I know its a 2x3 matrix..which the det. wouldn't apply since it is not square."
That's irrelevant- the problem doesn't say anything about the determinant of A (which doesn't exist) only the determinants of those 2 by 2 subsets.
Yeah i states how they had it though. sorry.
they said.. the det != 0
 
  • #4
Okay, now that we have that straightened out, exactly what is your definition of "rank"? What do you get if you "row reduce" A?
 
  • #5
the rank is the dimensions of the row space and column space of a matrix.
So when we do r-r-e, wherever we get leading ones, that is the rank #.
 

FAQ: Linear Algebra and rank problem.

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It involves the study of linear transformations, matrices, and systems of linear equations.

2. 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. It is a measure of the dimension of the vector space spanned by the rows or columns of the matrix. A matrix with full rank has linearly independent rows and columns and is therefore invertible.

3. Why is rank important in linear algebra?

The rank of a matrix is important because it provides information about the properties of the matrix and its solutions to systems of linear equations. It is also used to determine the dimension of the vector space spanned by the rows or columns of the matrix and to identify linearly independent vectors.

4. How is the rank of a matrix calculated?

The rank of a matrix can be calculated by performing row reduction operations on the matrix until it is in reduced row echelon form. The number of non-zero rows in the reduced matrix is equal to the rank of the original matrix.

5. What is the relationship between rank and linear independence?

The rank of a matrix is equal to the number of linearly independent rows or columns in the matrix. This means that a matrix with full rank has linearly independent rows and columns, and a matrix with rank less than its number of rows or columns has linearly dependent rows or columns.

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