Linear Dependence of x1, x2 and x3 in R^2

In summary, the vectors x1, x2, and x3 must be linearly dependent because x1 and x2 span R^2 and x3 can be written as a linear combination of these vectors. Additionally, the dimension of span (x1, x2, and x3) is 1, according to the book, but it could potentially be 3 if the vectors are all the same times a constant. The definition of dimension must be applied to determine the correct dimension.
  • #1
Dustinsfl
2,281
5
x1= column vector (2, 1)
x2= column vector (4, 3)
x3= column vector (7, -3)

Why must x1, x2, and x3 be linearly dependent?

x1 and x2 span R^2.
The basis are these two columns vectors: (3/2, -1/2), (-2, 1)

Since x1 and x2 form the basis, x3 can be written as a linear combination of these vectors.

Is that it? or correct?
 
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  • #2
Dustinsfl said:
x1= column vector (2, 1)
x2= column vector (4, 3)
x3= column vector (7, -3)

Why must x1, x2, and x3 be linearly dependent?

How to answer that question depends on what you have learned. What is the dimension of R2?
x1 and x2 span R^2.
The basis are these two columns vectors: (3/2, -1/2), (-2, 1)

There is no such thing as the basis for R2. Any two linearly independent vectors in R2 are a basis.
Since x1 and x2 form the basis, x3 can be written as a linear combination of these vectors.

Is that it? or correct?

You could just demonstrate x3 = cx1 + dx2; that would surely settle it.
 
  • #3
New question:
x1=(3, -2, 4)
x2=(3, -1, 4)
x3=(-6, 4, -8)

What is the dimension of span (x1, x2, and x3)

The book says 1; however, shouldn't the dimension be 3? I see that these 3 vectors are all the same times a constant but there are coordinates.
 
  • #4
Dustinsfl said:
New question:
x1=(3, -2, 4)
x2=(3, -1, 4)
x3=(-6, 4, -8)

What is the dimension of span (x1, x2, and x3)

The book says 1; however, shouldn't the dimension be 3? I see that these 3 vectors are all the same times a constant but there are coordinates.

If they are supposed to be a constant times each other you have mistyped something. But assuming that, what is the definition of dimension that you are using? You have to apply that.
 

What is linear dependence?

Linear dependence is a mathematical concept that describes the relationship between two or more variables in a linear system. In other words, it is the degree to which one variable can be predicted or determined by a combination of other variables.

How do you determine linear dependence?

To determine linear dependence, you can use various methods such as calculating the determinant of a matrix or performing a linear combination of the variables to see if they result in a zero vector. If the determinant is zero or the linear combination results in a zero vector, then the variables are linearly dependent.

What is the significance of linear dependence in R^2?

In R^2, linear dependence is essential because it helps us understand the relationship between two variables in a two-dimensional space. It also allows us to identify patterns and make predictions based on the values of the variables.

Can you have linear dependence in more than two variables?

Yes, it is possible to have linear dependence in more than two variables. In fact, linear dependence can exist in any number of variables as long as they can be expressed as a linear combination of each other.

How can linear dependence be avoided?

To avoid linear dependence, it is important to choose a set of variables that are independent of each other. This means that the variables should not be able to be expressed as a linear combination of each other. Additionally, using different types of variables (e.g. categorical and continuous) can also help avoid linear dependence.

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