Are These Vectors Linearly Dependent?

In summary, the vectors $\left[\begin{array}{r} 2\\ 1\\ -2 \end{array}\right], \left[\begin{array}{r} 0\\ 2\\ -2 \end{array}\right], \left[\begin{array}{r} 2\\ 3\\ -4 \end{array}\right]$ are linearly dependent. This is determined by the definition of "linearly dependent" and by using row reduction on the augmented matrix of the vectors. The purpose of the row reduction was to see if there exist numbers that satisfy the equations that define linearly dependent vectors. It is also possible to determine linear dependence through observation.
  • #1
karush
Gold Member
MHB
3,269
5
Are the vectors
$$\left[
\begin{array}{r}
2\\1\\-2
\end{array}\right]
,\quad
\left[\begin{array}{r}
0\\2\\-2
\end{array}\right]
,\quad
\left[\begin{array}{r}
2\\3\\-4
\end{array}\right]
$$
linearly dependent or linearly independent?
$$\left[ \begin{array}{rrr|r} 2 & 0 & 2 & 0 \\ 1 & 2 & 3 & 0 \\ -2 & -2 & -4 & 0 \end{array} \right]
\sim
\left[ \begin{array}{rrr|r} 1 & 0 & 1 & 0 \\ 0 & 1 & 1 & 0 \\ 0 & 0 & 0 & 0 \end{array} \right]$$
I assume this is independent due to trivial answers
 
Last edited:
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  • #2
Re: 12.1

By the definition of "linearly dependent", these vectors are linearly dependent if and only if there exist three number, a, b, and c, not all 0, such that
[tex]a\begin{bmatrix}2 \\ 1 \\ -2 \end{bmatrix}+ b\begin{bmatrix}0 \\ 2 \\ -2 \end{bmatrix}+ c\begin{bmatrix}2 \\ 3 \\ -4\end{bmatrix}= \begin{bmatrix}2a+ 2c \\ a+ 2b+ 3c \\ -2a- 2b- 4c \end{bmatrix}= \begin{bmatrix}0 \\ 0 \\ 0 \end{bmatrix}[/tex].

That is, 2a+ 2c= 0, a+ 2b+ 3c= 0, -2a- 2b- 4c= 0. From 2a+ 2c= 0, c= -a so the last two equations are a+ 2b- 3a= 2b- 2a= 0 and -2a- 2b+ 4c= 2a- 2b= 0. Both of those give a= b. Any numbers a, b, and c, such that b= a, c= -a will work.

So, yes, these vectors are linearly dependent.

You should think about two questions. What definition of "linearly independent" and "linearly dependent" did you learn? And what was your purpose in row reducing a matrix having the vectors as columns if you had to ask if the vectors were linearly dependent when you finished?
 
  • #3
Re: 12.1

I pretty much just followed an example
But probably could solve some of these just by observation
they used augmented matrix but only did some alteration
https://www.physicsforums.com/attachments/9045
 
Last edited:
  • #4
I edited the thread title. The original title of "12.1" wasn't of much use to describe the topic. :)
 
  • #5
Thank you

I tried also to change it

But when I submitted it didn't happen
 

FAQ: Are These Vectors Linearly Dependent?

What is linear dependence?

Linear dependence refers to a mathematical relationship between two or more variables where one variable can be expressed as a linear combination of the others. In other words, if one variable can be written as a multiple of the others, they are considered linearly dependent.

How is linear dependence different from linear independence?

Linear dependence and linear independence are two opposite concepts. Linear independence refers to a mathematical relationship between variables where none of the variables can be expressed as a linear combination of the others. In other words, they are all unique and necessary to describe the relationship.

What is the importance of studying linear dependence?

Linear dependence is an important concept in mathematics and science as it helps us understand the relationships between variables and how they affect each other. It is also used in various fields such as economics, engineering, and physics to model and analyze real-world phenomena.

How do you determine if a set of vectors is linearly dependent?

To determine if a set of vectors is linearly dependent, you can perform a few tests. One method is to check if any of the vectors can be written as a linear combination of the others. Another method is to find the determinant of the matrix formed by the vectors. If the determinant is equal to 0, the vectors are linearly dependent.

Can a set of linearly dependent vectors be used to form a basis?

No, a set of linearly dependent vectors cannot be used to form a basis. A basis is a set of linearly independent vectors that can span the entire vector space. Since linearly dependent vectors can be expressed as multiples of each other, they cannot be used to represent all possible combinations in the vector space.

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