Linear Dependence: Is (1,0,0), (-3,7,0) & (1,1,0) Independent?

In summary, you can work out the linear combinations by solving equations for a and b and then subtracting one equation from the other.
  • #1
forty
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(1,0,0) (-3,7,0) and (1,1,0)

I'm trying to work out if these vectors are linearly independent or not.
Intuitively i believe they are dependent as they span the xy-plane.. but then how do i work out the linear combinations.

e.g:
(1,0,0) = a(-3,7,0) + b(1,1,0) where a and b are real numbers.

Ive tried writing the vectors as column vectors, then row reducing and i end up with

[1 -10 0;0 7 1;0 0 0] (which has rank(2) which means they are linearly dependent)

but as for where to go from here I'm lost.

Any help greatly appreciated.
 
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  • #2
forty said:
(1,0,0) (-3,7,0) and (1,1,0)

I'm trying to work out if these vectors are linearly independent or not.
Intuitively i believe they are dependent as they span the xy-plane.. but then how do i work out the linear combinations.

e.g:
(1,0,0) = a(-3,7,0) + b(1,1,0) where a and b are real numbers.
Okay, so 1= -3a+ b and 0= 7a+b. Solve those two equations for a and b. I would recommend subtracting one equation from the other!

Ive tried writing the vectors as column vectors, then row reducing and i end up with

[1 -10 0;0 7 1;0 0 0] (which has rank(2) which means they are linearly dependent)

but as for where to go from here I'm lost.

Any help greatly appreciated.
 
  • #3
Is there a way of doing this with matrices?

So writing the vectors as columns and row reducing, and from here deciding what are the linear combinations?

so [1 -3 1;0 7 1;0 0 0]

becomes [1 -10 0;0 7 1;0 0 0]from here is there a way of getting the answer directly from this matrix?
 
  • #4
You prefer a harder way? Writing the two equations, 1= -3a+ b and 0= 7a+ b as an "augmented" matrix gives
[tex]\left[\begin{array}{ccc}-3 & 1 & 1\\ 7 & 1 & 0\end{array}\right][/tex]
where, as you can see, the vectors form the rows. That row reduces to
[tex]\left[\begin{array}{ccc} 1 & 0 & -\frac{1}{10} \\ 0 & 1 & \frac{7}{10}\end{array}\right[/tex]
showing that the equations have a solution (a= -1/10 and b= 7/10) and so the vectors are dependent. As for your initial method, the very fact that your matrix has rank only two tells you that the vectors are dependent.

Writing the
 
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  • #5
Once again thank you! you are my new Walter Lewin!
 

Related to Linear Dependence: Is (1,0,0), (-3,7,0) & (1,1,0) Independent?

1. What is linear dependence?

Linear dependence is a mathematical concept that describes the relationship between two or more vectors in a vector space. It refers to the situation where one vector can be expressed as a linear combination of other vectors in the space.

2. How do you determine if three vectors are linearly independent?

To determine if three vectors are linearly independent, we can use the determinant method or the rank method. The determinant method involves constructing a matrix with the three vectors as columns and finding the determinant. If the determinant is non-zero, the vectors are linearly independent. The rank method involves forming a matrix with the three vectors as rows and finding the rank. If the rank is equal to the number of vectors, then they are linearly independent.

3. Are (1,0,0), (-3,7,0) & (1,1,0) linearly dependent?

Yes, these three vectors are linearly dependent. Using the determinant method, we can see that the determinant of the matrix formed by these vectors is equal to 0. This means that the vectors are not linearly independent and can be expressed as a linear combination of each other.

4. Can a set of linearly dependent vectors be reduced to a linearly independent set?

Yes, a set of linearly dependent vectors can be reduced to a linearly independent set by removing redundant vectors. This can be done by finding the rank of the matrix formed by the vectors and removing the vectors that do not contribute to the rank. The remaining vectors will form a linearly independent set.

5. Why is linear dependence important in mathematics and science?

Linear dependence is important in mathematics and science because it helps us understand and analyze relationships between different quantities or variables. It is also used in many applications, such as solving systems of equations, data analysis, and machine learning. Additionally, the concept of linear dependence is closely related to other important concepts in mathematics, such as span, basis, and dimension.

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