How to find a linearly independent vector?

In summary, to find a linearly independent set of vectors that spans the same subspace of R^3, you can eliminate one vector and then check if the remaining two are independent. If they are, they can serve as a basis for the subspace.
  • #1
UrbanXrisis
1,196
1
Find a linearly independent set of vectors that spans the same subspace of R^3 as that spanned by the vectors

[tex] \left(\begin{array}{c} -2 & -1 & -2 \end{array}\right) ,

\left(\begin{array}{c} -2 & 3 & -8 \end{array}\right) ,

\left(\begin{array}{c} 0 & -2 & 3 \end{array}\right)

[/tex]


I'm not sure how to find a linearly independent vector. For a linearly dependency, the determinant of the matrix cannot equal zero. But how would i find two other 3x1 vectors that does not have linear dependency?
 
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  • #2
You could row reduce and look at the columns that correspond to the leading columns of your reduced matrix. Can you see why this would mean they're independent?
 
  • #3
Since there is a zero (in the third vector) which simplifies calculations, you can just check to see if any of the three vectors can be formed as a linear combination of the other two. If yes, eliminate anyone of the vectors.
It will then become immediately clear if the two remaining vectors are linearly independent or not!
Having confirmed the linear independence of the two remaining vectors, the spanning property follows. You now have a set of basis vectors for this vector space!
 
Last edited:

1. How do I determine if two vectors are linearly independent?

To determine if two vectors are linearly independent, you can use the determinant method. Set the two vectors as the columns of a 2x2 matrix and find the determinant. If the determinant is non-zero, then the vectors are linearly independent. If the determinant is zero, then the vectors are linearly dependent.

2. Can three or more vectors be linearly independent?

Yes, three or more vectors can be linearly independent. To determine if three or more vectors are linearly independent, you can use the rank method. Arrange the vectors as the rows of a matrix and find the rank of the matrix. If the rank is equal to the number of vectors, then they are linearly independent. If the rank is less than the number of vectors, then they are linearly dependent.

3. How can I find a linearly independent vector from a set of given vectors?

To find a linearly independent vector from a set of given vectors, you can use the Gram-Schmidt process. This process involves taking the first vector as the initial basis, then subtracting the projections of the other vectors onto this basis to get an orthogonal vector. Repeat this process for the remaining vectors until you have a set of linearly independent vectors.

4. Can a zero vector be linearly independent?

No, a zero vector cannot be linearly independent. A vector is considered linearly independent if it cannot be written as a linear combination of other vectors. Since the zero vector is a scalar multiple of any other vector, it can always be expressed as a linear combination and is therefore linearly dependent.

5. Is it possible for two linearly independent vectors to be parallel?

No, two linearly independent vectors cannot be parallel. If two vectors are parallel, then one is a scalar multiple of the other and they are therefore linearly dependent. Linearly independent vectors must have different directions and cannot be parallel.

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