Linear independence if there is a column of zeros

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A column of zeros in a matrix indicates that the matrix is linearly dependent, as it implies that at least one vector can be expressed as a linear combination of others. However, the presence of a zero column does not affect the linear independence of the rows in the context of a system of equations. Each row represents a different equation, and the system is independent if row reduction does not yield a row of zeros. The matrix itself is not a vector; it belongs to a higher-dimensional vector space. Clarifying the specific context of the question is essential for accurate responses.
ti-84minus
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Homework Statement


If, in a matrix, there is a column of all zeros, does this mean the given vector/matrix is linearly dependent?
An example would be:
[1 2 0 4]
[2 3 0 1]
[5 2 0 7]

A few questions to clear up some possible misconceptions:
1) The matrix above is a 4-dimensional vector?
2) The given vector has 4 unknowns, but a column of zeros, therefore the system is linearly dependent.

Thanks for your help!
 
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I don't think the matrix you have is a vector, vectors are either row vectors (1xm matrices) or column vectors (nx1 matrices). For this system of linear equations, each row represents a different equation. The system is then linearly independent if each row is independent, ie. row reduction doesn't yield a row of zeros. A column of zeros doesn't affect this linear independence. This is what it affects: if you take a 4x1 column vector, say [a,b,c,d]^T, and multiply it on the left by your matrix, it maps this vector to a 3x1 vector based on the column vectors of your matrix. The zero-column (3rd column) of your matrix maps the third row of your [a,b,c,d]^T to 0 in all rows of its image, which ends up being [a+2b+4d,2a+3b+d,5a+2b+7d]^T.
 
ti-84minus said:

Homework Statement


If, in a matrix, there is a column of all zeros, does this mean the given vector/matrix is linearly dependent?
A set of vectors can be linearly dependent or linearly independent, but it doesn't usually make any sense to describe a single vector as being dependent or independent.
ti-84minus said:
An example would be:
[1 2 0 4]
[2 3 0 1]
[5 2 0 7]

A few questions to clear up some possible misconceptions:
1) The matrix above is a 4-dimensional vector?
No. The matrix on its own belongs to a vector space of dimension 12. The rows of the matrix are vectors in R4, a 4-dimensional vector space. The columns of the matrix are vectors in R3, a 3-dimensional vector space.
ti-84minus said:
2) The given vector has 4 unknowns, but a column of zeros, therefore the system is linearly dependent.
What given vector? Does the matrix above represent a system of three equations in four unknowns?

You need to be more specific about what you're asking before we can give meaningful answers.
ti-84minus said:
Thanks for your help!
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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