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

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Discussion Overview

The discussion revolves around the properties of a 3x3 matrix, specifically focusing on the concepts of rank, nullity, and the geometric interpretations of the column space, null space, and row space. Participants are tasked with providing examples and proofs related to these concepts.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant requests an example of a 3x3 matrix whose column space is a plane through the origin in 3-space, along with the geometric nature of the null space and row space.
  • Another participant notes that the equality of row rank and column rank seems to follow immediately, suggesting a connection between these concepts.
  • A participant expresses the need for a clear explanation of the proof regarding the linear dependence of row or column vectors in non-square matrices.
  • Further, a participant provides a specific example using a 2x3 matrix, arguing that its row vectors must be linearly dependent due to the dimensionality of the space.
  • Another participant emphasizes the need for more effort in understanding the proofs and asks what the original poster has attempted to solve the problem.

Areas of Agreement / Disagreement

Participants appear to be engaged in a collaborative exploration of the concepts, with some expressing the need for clarification and proof, while others provide insights and examples. There is no clear consensus on the examples or proofs presented, indicating ongoing discussion and exploration.

Contextual Notes

Participants assume the entries of the matrices are real numbers, and there is an implicit understanding of linear algebra concepts such as vector spaces and linear dependence. The discussion does not resolve the mathematical steps required for the proofs or examples.

Who May Find This Useful

Students and educators in linear algebra, particularly those interested in matrix theory, vector spaces, and geometric interpretations of linear transformations.

Swati
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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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