Linear Independence and Rank - Linear Algebra
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What is the dimension of the space spanned by the following vectors:



What is the dimension of the space spanned by the following vectors:
Since there are three linearly independent vectors, they span a 3 dimensional space.
Notice that the vectors each have 5 coordinates to them. Therefore they actually span a 3 dimensional subspace of a 5 dimensional space.
Since there are three linearly independent vectors, they span a 3 dimensional space.
Notice that the vectors each have 5 coordinates to them. Therefore they actually span a 3 dimensional subspace of a 5 dimensional space.
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In a 5 dimensional vector space, what is the maximum number of vectors you can have in a linearly dependent set?
In a 5 dimensional vector space, what is the maximum number of vectors you can have in a linearly dependent set?
Linearly dependent sets have no limit to the number of vectors they can have.
Linearly dependent sets have no limit to the number of vectors they can have.
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Consider the following set of three vectors:

where 
Is the set linearly independent?
Consider the following set of three vectors:
where
Is the set linearly independent?
Since
can be written as a linear combination of of
and
then the set cannot be linearly independent.
Since can be written as a linear combination of of
and
then the set cannot be linearly independent.
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Does the following row reduced echelon form of a matrix represent a linearly independent set?

Does the following row reduced echelon form of a matrix represent a linearly independent set?
The set is linearly dependent because there is a row of all zeros.
Notice that having columns of all zeros does not tell if the set is linearly independent or not.
The set is linearly dependent because there is a row of all zeros.
Notice that having columns of all zeros does not tell if the set is linearly independent or not.
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Does the following row reduced echelon form of a matrix represent a linearly independent set?

Does the following row reduced echelon form of a matrix represent a linearly independent set?
The set must be linearly independent because there are no rows of all zeros. There are columns of all zeros, but columns do not tell us if the set is linearly independent or not.
The set must be linearly independent because there are no rows of all zeros. There are columns of all zeros, but columns do not tell us if the set is linearly independent or not.
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Consider a set of 3 vectors from a 3 dimensional vector space.
Is the set linearly independent?
Consider a set of 3 vectors from a 3 dimensional vector space.
Is the set linearly independent?
It depends on what the vectors are.
For example, if



Then the set is linearly independent.
However if the vectors were



then the set would be linearly dependent.
It depends on what the vectors are.
For example, if
Then the set is linearly independent.
However if the vectors were
then the set would be linearly dependent.
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Consider a set of 3 vectors from a 2 dimensional vector space.
Is the set linearly independent?
Consider a set of 3 vectors from a 2 dimensional vector space.
Is the set linearly independent?
Since the dimension of the space is 2, a linearly independent set can have at most two vectors. Since the set in consideration has 3 and 3>2, the set must be linearly dependent.
Since the dimension of the space is 2, a linearly independent set can have at most two vectors. Since the set in consideration has 3 and 3>2, the set must be linearly dependent.
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Determine whether the following vectors in Matrix form are Linearly Independent.

Determine whether the following vectors in Matrix form are Linearly Independent.
To figure out if the matrix is independent, we need to get the matrix into reduced echelon form. If we get the Identity Matrix, then the matrix is Linearly Independent.





















Since we got the Identity Matrix, we know that the matrix is Linearly Independent.
To figure out if the matrix is independent, we need to get the matrix into reduced echelon form. If we get the Identity Matrix, then the matrix is Linearly Independent.
Since we got the Identity Matrix, we know that the matrix is Linearly Independent.
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Find the rank of the following matrix.

Find the rank of the following matrix.
We need to get the matrix into reduced echelon form, and then count all the non all zero rows.














The rank is 2, since there are 2 non all zero rows.
We need to get the matrix into reduced echelon form, and then count all the non all zero rows.
The rank is 2, since there are 2 non all zero rows.
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Calculate the Rank of the following matrix

Calculate the Rank of the following matrix
We need to put the matrix into reduced echelon form, and then count all the non-zero rows.


Since there is only 1 non-zero row, the Rank is 1.
We need to put the matrix into reduced echelon form, and then count all the non-zero rows.
Since there is only 1 non-zero row, the Rank is 1.
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Determine if the following matrix is linearly independent or not.

Determine if the following matrix is linearly independent or not.
Since the matrix is
, we can simply take the determinant. If the determinant is not equal to zero, it's linearly independent. Otherwise it's linearly dependent.

Since the determinant is zero, the matrix is linearly dependent.
Since the matrix is , we can simply take the determinant. If the determinant is not equal to zero, it's linearly independent. Otherwise it's linearly dependent.
Since the determinant is zero, the matrix is linearly dependent.
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If matrix A is a 5x8 matrix with a two-dimensional null space, what is the rank of A?
If matrix A is a 5x8 matrix with a two-dimensional null space, what is the rank of A?
Given that rank A + dimensional null space of A = total number of columns, we can determine rank A = total number of columns-dimensional null space of A. Using the information given in the question we can solve for rank A:

Given that rank A + dimensional null space of A = total number of columns, we can determine rank A = total number of columns-dimensional null space of A. Using the information given in the question we can solve for rank A:
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If matrix A is a 10x12 matrix with a three-dimensional null space, what is the rank of A?
If matrix A is a 10x12 matrix with a three-dimensional null space, what is the rank of A?
Given that rank A + dimensional null space of A = total number of columns, we can determine rank A = total number of columns-dimensional null space of A. Using the information given in the question we can solve for rank A:

Given that rank A + dimensional null space of A = total number of columns, we can determine rank A = total number of columns-dimensional null space of A. Using the information given in the question we can solve for rank A:
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What is the dimension of the space spanned by the following vectors:



What is the dimension of the space spanned by the following vectors:
Since there are three linearly independent vectors, they span a 3 dimensional space.
Notice that the vectors each have 5 coordinates to them. Therefore they actually span a 3 dimensional subspace of a 5 dimensional space.
Since there are three linearly independent vectors, they span a 3 dimensional space.
Notice that the vectors each have 5 coordinates to them. Therefore they actually span a 3 dimensional subspace of a 5 dimensional space.
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Determine the row rank of the matrix

Determine the row rank of the matrix
To determine the matrix, we turn the matrix into reduced row echelon form
By adding
times the first row to the second we get

And find that the row rank is 
To determine the matrix, we turn the matrix into reduced row echelon form
By adding times the first row to the second we get
And find that the row rank is
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Determine the row rank of the matrix

Determine the row rank of the matrix
To determine the row rank of the matrix we reduce the matrix into reduced echelon form.
First we add
times the 1st row to the 2nd row

add
times the 1st row to the 3rd row

Switch the 2nd row and the 3rd row

multiply the 2nd row by 

add
times the 2nd row to the 1st row

And we find that the row rank is 
To determine the row rank of the matrix we reduce the matrix into reduced echelon form.
First we add times the 1st row to the 2nd row
add times the 1st row to the 3rd row
Switch the 2nd row and the 3rd row
multiply the 2nd row by
add times the 2nd row to the 1st row
And we find that the row rank is
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Consider the following set of vectors



Is the the set linearly independent?
Consider the following set of vectors
Is the the set linearly independent?
Yes, the set is linearly independent. There are multiple ways to see this
Way 1) Put the vectors into matrix form,

The matrix is already in reduced echelon form. Notice there are three rows that have a nonzero number in them and we started with 3 vectors. Thus the set is linearly independent.
Way 2) Consider the equation 
If when we solve the equation, we get
then it is linearly independent. Let's solve the equation and see what we get.


Distribute the scalar constants to get

Thus we get a system of 3 equations



Since
the vectors are linearly independent.
Yes, the set is linearly independent. There are multiple ways to see this
Way 1) Put the vectors into matrix form,
The matrix is already in reduced echelon form. Notice there are three rows that have a nonzero number in them and we started with 3 vectors. Thus the set is linearly independent.
Way 2) Consider the equation
If when we solve the equation, we get then it is linearly independent. Let's solve the equation and see what we get.
Distribute the scalar constants to get
Thus we get a system of 3 equations
Since the vectors are linearly independent.
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Consider the following set of vectors





Is the the set linearly independent?
Consider the following set of vectors
Is the the set linearly independent?
The vectors have dimension 3. Therefore the largest possible size for a linearly independent set is 3. But there are 4 vectors given. Thus, the set cannot be linearly independent and must be linearly dependent
Another way to see this is by noticing that
can be written as a linear combination of the other vectors:

The vectors have dimension 3. Therefore the largest possible size for a linearly independent set is 3. But there are 4 vectors given. Thus, the set cannot be linearly independent and must be linearly dependent
Another way to see this is by noticing that can be written as a linear combination of the other vectors:
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In a vector space with dimension 5, what is the maximum number of vectors that can be in a linearly independent set?
In a vector space with dimension 5, what is the maximum number of vectors that can be in a linearly independent set?
The dimension of a vector space is the maximum number of vectors possible in a linearly independent set. (notice you can have linearly independent sets with 5 or less, but never more than 5)
The dimension of a vector space is the maximum number of vectors possible in a linearly independent set. (notice you can have linearly independent sets with 5 or less, but never more than 5)
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In a vector space of dimension 5, can you have a linearly independent set of 3 vectors?
In a vector space of dimension 5, can you have a linearly independent set of 3 vectors?
The dimension of the vector space is the maximum number of vectors in a linearly independent set. It is possible to have linearly independent sets with less vectors than the dimension.
So for this example it is possible to have linear independent sets with
1 vector, or 2 vectors, or 3 vectors, all the way up to 5 vectors.
The dimension of the vector space is the maximum number of vectors in a linearly independent set. It is possible to have linearly independent sets with less vectors than the dimension.
So for this example it is possible to have linear independent sets with
1 vector, or 2 vectors, or 3 vectors, all the way up to 5 vectors.
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