Proving That Any Vector in a Vector Space V Can Be Written as a Linear Combination of a Basis Set

In summary: So what can you say about a given vector? Can it be linearly independent from your basis? Or otherwise, what does it mean it can't?
  • #1
kregg87
5
1

Homework Statement


Show that any vector in a vector space V can be written as a linear combination of a basis set for that same space V.

Homework Equations


http://linear.ups.edu/html/section-VS.html
We are suppose to use the 10 rules in the above link, plus the fact that if you have a lineraly independent set
{X1,X2,...,Xn} then -> c1X1+c2X2+...+cnXn = 0 vector implies that all the constants (c1,c2, etc) are zero.

Not looking for a complete solution, just not sure where to start. I've tried proof by contradiction and a couple other ways and non have worked out for me.

The Attempt at a Solution

 
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  • #2
kregg87 said:

Homework Statement


Show that any vector in a vector space V can be written as a linear combination of a basis set for that same space V.

Homework Equations


http://linear.ups.edu/html/section-VS.html
We are suppose to use the 10 rules in the above link, plus the fact that if you have a lineraly independent set
{X1,X2,...,Xn} then -> c1X1+c2X2+...+cnXn = 0 vector implies that all the constants (c1,c2, etc) are zero.

Not looking for a complete solution, just not sure where to start. I've tried proof by contradiction and a couple other ways and non have worked out for me.

The Attempt at a Solution


Define "basis". (I know the usual definition, but what is the one YOU are using?)
 
  • #3
Ray Vickson said:
Define "basis". (I know the usual definition, but what is the one YOU are using?)
My definition is a linearly independent set of N vectors, where N in the dimension of the space. My definition of dimension, N, is it the max number of mutually lineraly independant vectors possible.
 
  • #4
kregg87 said:
My definition is a linearly independent set of N vectors, where N in the dimension of the space. My definition of dimension, N, is it the max number of mutually lineraly independant vectors possible.
So what can you say about a given vector? Can it be linearly independent from your basis? Or otherwise, what does it mean it can't?
 

1. What is a vector space V?

A vector space V is a set of vectors that satisfy certain properties, such as closure under addition and scalar multiplication. These properties allow for operations like vector addition and scalar multiplication to be defined within the vector space.

2. What is a basis set?

A basis set for a vector space V is a set of vectors that are linearly independent and span the entire vector space. This means that any vector in V can be written as a linear combination of the basis vectors.

3. How do you prove that any vector in V can be written as a linear combination of a basis set?

To prove this, you can use the fact that a basis set spans the entire vector space. This means that any vector in V can be written as a linear combination of the basis vectors. You can also use the fact that a basis set is linearly independent, which means that no vector in the set can be written as a linear combination of the other vectors in the set.

4. Why is it important to prove this property of vector spaces?

Proving this property is important because it shows that the basis set is a fundamental part of the vector space. It also allows for a more efficient way to represent vectors, as any vector in the space can be written as a linear combination of a smaller set of basis vectors.

5. Can this property be applied to any vector space?

Yes, this property can be applied to any vector space. As long as the vector space satisfies the properties of closure under addition and scalar multiplication, a basis set can be defined and this property can be proven.

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