MHB Rank & Nullity: 3x3 Matrix w/ Plane Origin & LD Vectors

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A 3x3 matrix can be constructed where its column space represents a plane through the origin in 3D space, indicating that the matrix has a rank of 2. The null space of this matrix is a line, while the row space is also a plane, reflecting the geometric relationships between these spaces. It is established that if a matrix A is not square, either the row vectors or the column vectors must be linearly dependent due to the limitations imposed by their respective dimensions. For example, in a 2x3 matrix, the three row vectors in R^2 must be linearly dependent since the maximum dimension is 2. This discussion emphasizes the importance of understanding the relationships between matrix dimensions and their corresponding vector spaces.
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1.(a) Give an example of 3*3 matrix whose column space is a plane through the origin in 3-space
(b) what kind of geometry object is the null space and row space of your matrix

2. Prove that if a matrix A is not square, then either the row vectors or the column vectors of A are linearly dependent.
 
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#2 rowrank(A) = columnrank(A) -- seems to follow immediately.
 
we have to prove. please explain clearly.
 
Swati said:
1.(a) Give an example of 3*3 matrix whose column space is a plane through the origin in 3-space
(b) what kind of geometry object is the null space and row space of your matrix

2. Prove that if a matrix A is not square, then either the row vectors or the column vectors of A are linearly dependent.
I assume that the entries of the matrices are reals.
Q2. Consider a 2x3 matrix. Let its row vectors be (a,b), (c,d),(e,f). So we got 3 vectors from $\mathbb{R}^2$. They have to be linearly dependent since dimension of $\mathbb{R}^2$ is 2. Can you generalize?
 
Swati said:
we have to prove. please explain clearly.
More effort on your part is required. What have you tried and what don't you understand.
 
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