K cannot be what, if you want this matrix to form a basis, confused

In summary, the conversation discusses the conditions for a set of vectors to form a basis for R^3. It is determined that the first two columns of the given matrix are linearly independent, but the third column with k in it needs to be checked separately. The quickest way to determine if k satisfies the condition is to check for a solution of Mx=0, which will imply that x=0. It is also noted that the matrix itself is not a basis of R^3.
  • #1
mr_coffee
1,629
1
4 -4 4
-5 6 -3
0 4 k
form a basis for R^3 if and only if k != ?
since the last col has a k in it, i wanted to see if the first 2 colmuns are linear indepdant, adn they are, becuase i row reduced w/calculator:
4 -4 0
-5 6 0
0 4 0
and got
1 0 0
0 1 0
0 0 0
is there a quick way to figure out the k, without mantually row reducing with k? Also if there isn't a quick way, what am i going to be looking for? it will span R^3 if i get
0
0
1
for the last col with k in it. Thanks.
 
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  • #2
You don't *have* to get down to 1's, merely linearly independent rows/cols, 1s are just nice. And it's better if you say "when do the rows/cols form a basis", rather than "when is the matrix a basis of R^3": the matirx is never a basis of R^3; it isn't even an element of R^3.

Remember, you're just looking for a solution of Mx=0 to imply x=0, so that's an easy criterion to check when there is only 1 variable (k) to check
 

FAQ: K cannot be what, if you want this matrix to form a basis, confused

What does it mean for K to not be able to form a basis in a matrix?

When we say that K cannot form a basis in a matrix, it means that the set of vectors in K does not span the entire space. In other words, there are some vectors in the space that cannot be expressed as a linear combination of the vectors in K. This can also be interpreted as K not being a linearly independent set.

Why is it important for a matrix to have a basis?

A basis is a set of linearly independent vectors that span the entire space. This means that any vector in the space can be expressed as a linear combination of the basis vectors. Having a basis is important because it allows us to easily represent and manipulate vectors in a space. It also helps us to understand the dimensionality of the space and to solve systems of linear equations.

Can a matrix have multiple bases?

Yes, a matrix can have multiple bases. This is because there can be different sets of linearly independent vectors that span the same space. However, all bases for a given space will have the same number of vectors, known as the dimension of the space.

How do you determine if a set of vectors forms a basis in a matrix?

To determine if a set of vectors forms a basis in a matrix, we need to check two conditions: linear independence and span. If the vectors in the set are linearly independent and span the entire space, then they form a basis. One way to check for linear independence is to perform row reduction on the matrix and check for any rows of zeros. If there are no rows of zeros, then the vectors are linearly independent. To check for span, we can perform Gaussian elimination and see if we can obtain all the vectors in the space using the vectors in our set.

Can a matrix have an infinite number of basis vectors?

No, a matrix cannot have an infinite number of basis vectors. This is because the number of basis vectors is equal to the dimension of the space, which is a finite number. If a matrix has an infinite number of basis vectors, then it would have an infinite number of dimensions, which is not possible.

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