Solving a Basis Problem in R^2

In summary, the conversation discusses the concept of forming a basis for R^2, which is a set of vectors that are linearly independent and span R^2. It is shown that the vectors (1,1) and (1,-1) satisfy this property and any vector in R^2 can be expressed as a linear combination of these vectors. The conversation also explains the meaning of the calculations done to find the constants a1 and b1 in the linear combination.
  • #1
Chadlee88
41
0
Hey, I've done this problem but i don't know what it all means? What does it mean to form a basis?:confused:

Problem: show that the vectors (1,1) , (1, -1) form a basis for R^2

(x,y) = a1(1, 1) + b1(1, -1)
x = a1 + b1 => a1 = x - b1
y= a1- b1 => b1 = a1-y

a1 = x - a1 + y
2a1 = x + y
a1 = 1/2(x + y) <----- What does this represent?

b1 = (x-b1)-y
2b1 = x - y
b1 = 1/2(x-y) <----- What does this represent?
 
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  • #2
Do you know the defintion of basis/bases and span? Do you know what scalar/magnitude are?
 
  • #3
Ok. A "basis for R²" is a set B of vectors of R² that...

(1) ...are linearly independant and...

(2) ...such that any vector (x,y) of R² can be expressed as a linear combination of the vectors of the set B. (A set of vector that have property (2) is said to span R².)

It can be shown that any set of n vectors which span R^n are automatically linearly independant. So you only have to verify property (2) since it implies (1).

What you've done (without realizing it, perhaps), is you've said, if {(1,1), (1,-1)} spans R², then it must be that for any vector (x,y) of R², we can write it as a linear combination of (1,1) and (1,-1). In other words, there exists two constants a1 and b1 such that (x,y)=a1(1,1)+b1(1,-1). You've then manipulated this expression to express a1 and b1 in terms of x and y. By doing this, you proved that indeed, given a vector (x,y), there are constants a1 and b1 such that (x,y)=a1(1,1)+b1(1,-1) and they are given by a1 = (x + y)/2, b1 = (x-y)/2.

It takes practice and perseverance to integrate all the subtleties of mathematical proofs, but I hope my explanation was helpful.
 
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  • #4
quasar987 said:
It can be shown that any set of n vectors which span R^n are automatically linearly independant. So you only have to verify property (2) since it implies (1).
This is actually an if and only if as the converse holds as well. ie: any set of n vectors in R^n which is linearly independent spans R^n.

So as an alternative to what quasar suggested, you could just show that (1, 1), (1, -1) are linearly independent which amounts to showing that one is not a scalar multiple of the other since there are only two vectors.
 
  • #5
Another way of looking at "basis" is that any vector can be written as a linear combination of the basis vectors in a unique way.

The fact that any vector can be written as a linear combination of the basis vectors is due to their spanning[/b] the space. The fact that that linear combination is unique is due to their being independent.

a1 = 1/2(x + y) <----- What does this represent?
b1 = 1/2(x-y) <----- What does this represent?
You started by asserting that an arbitrary vector, (x, y), could be written as a linear combination of the vectors (1, 1) and (1, -1):
(x,y)= a1(1, 1)+ b1(1,-1) for some real numbers a1 and b1. You have succeeded in showing how to calculate those numbers thus showing
(1) that the numbers exist, that (x,y) can be written as such a linear combination.
(2) that the numbers are unique, since the formulas you show are functions and have only one result, thus showing that the linear combination is unique.
 

FAQ: Solving a Basis Problem in R^2

1. What is a Basis Problem in R^2 and why is it important to solve?

A Basis Problem in R^2 refers to finding a set of linearly independent vectors that span the two-dimensional space. It is important to solve because it allows us to represent any point in the two-dimensional space using a combination of these basis vectors, making it easier to perform calculations and solve problems.

2. How can I determine if a set of vectors form a basis in R^2?

To determine if a set of vectors form a basis in R^2, we need to check if they are linearly independent and if they span the entire two-dimensional space. This can be done by creating a matrix with the given vectors as columns and checking if the determinant of the matrix is non-zero.

3. Can I use the Gram-Schmidt process to solve a Basis Problem in R^2?

Yes, the Gram-Schmidt process can be used to find a set of orthogonal vectors from a given set of linearly independent vectors. These orthogonal vectors can then be used as the basis vectors for the two-dimensional space.

4. Is there a unique solution to a Basis Problem in R^2?

No, there can be multiple solutions to a Basis Problem in R^2. This is because there can be more than one set of linearly independent vectors that can span the two-dimensional space. However, any set of basis vectors will be valid solutions to the problem.

5. Can I use software packages like R to solve a Basis Problem in R^2?

Yes, R has built-in functions and packages that can help solve a Basis Problem in R^2. For example, the "pracma" package has a function called "qrGramSchmidt" which can perform the Gram-Schmidt process and find the basis vectors for a given set of vectors in R^2.

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