Vector Space Prob: Show Linear Dependence

In summary: From there, you can show that a set of vectors is linearly dependent if and only if any one of the vectors can be written as a linear combination of the others.
  • #1
Raghav Gupta
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Show that a set of vectors are linearly dependent if and only if anyone of the vectors can be represented as linear combination of the remaining vectors.

I don't know these terms. Vectors I know apart from that other terms. Can someone provide some information in any form for solving this question.
 
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  • #2
Any vector A can be written as a sum of basis vectors and magnitudes as in ## A = \sum_{i=1}^n a_i \vec e _i##. In common practice, you will see them as ##A = a_x \hat x + a_y \hat y + a_z \hat z## for 3D space.
A linear dependent set of vectors, I only know by the definition you posted. However, a linearly independent set of k vectors can be defined by the fact that they span a k - dimensional space.
A linear combination of vectors ##\{ \vec v_i \} _{i=1}^N## is any combination of coefficients ##x_i, i=1...N##, in the form ## \vec L = \sum_{i=1}^N x_i \vec v _i##.

Linear independence has been defined by there being only one set of x_i 's that can make ##\vec L = 0## and that is for all the x_i's to be zero.

For this problem, you are to show that if a set of vectors is linearly dependent, then at least one of the vectors can be written as a linear combination of the others; and if one of the vectors can be written as a linear combination of the others then set of vectors is linearly dependent.

You will need to know what the question is assuming you know as the definition of linearly dependent vectors.

If a set of N vectors is linearly dependent, then at most it can span N-1 dimensions...you could use this to show that it must be a linear combination of the other vectors.
 
  • #3
Raghav Gupta said:
Show that a set of vectors are linearly dependent if and only if anyone of the vectors can be represented as linear combination of the remaining vectors.

I don't know these terms. Vectors I know apart from that other terms. Can someone provide some information in any form for solving this question.

Start by looking up the terms.
 
  • #4
micromass said:
Start by looking up the terms.
Yes. Every linear algebra textbook defines the terms "linearly dependent," "linearly independent," and "linear combination."
 

Related to Vector Space Prob: Show Linear Dependence

What is a vector space?

A vector space is a mathematical structure that consists of a set of elements, called vectors, and two operations - addition and scalar multiplication - that satisfy certain axioms. Vectors in a vector space can be added together and multiplied by scalars, resulting in another vector within the same vector space.

What does it mean for vectors to be linearly dependent?

Two or more vectors in a vector space are considered to be linearly dependent if one of the vectors can be expressed as a linear combination of the others. In other words, if one vector can be written as a scalar multiple of another vector, then the vectors are linearly dependent.

How do you show that vectors are linearly dependent?

To show that vectors are linearly dependent, you can use the concept of a linear combination. If you can find a set of coefficients that, when multiplied by each vector and added together, result in the zero vector, then the vectors are linearly dependent. This can be represented in a system of linear equations, where the coefficients are the unknown variables.

Why is it important to determine if vectors are linearly dependent?

Determining linear dependence is important in many areas of mathematics and science, particularly in linear algebra and vector calculus. It allows us to understand the relationships between vectors and can be used to solve systems of equations and perform other mathematical operations.

How is linear dependence related to the dimension of a vector space?

The dimension of a vector space is equal to the number of linearly independent vectors in that space. If there is more than one linearly dependent vector in a set, then the dimension of the vector space will be less than the number of vectors in the set. Therefore, linear dependence is closely related to the dimension of a vector space.

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