Solving Linear Dependence of a Matrix

In summary, the conversation revolved around the use of matrices in solving problems related to linear dependence and independence. The person reviewing matrices was confused about a particular question and sought help in understanding the solution provided by their calculator. The question involved determining a non-trivial linear relation between column vectors and using a homogeneous system to solve it. There were discussions on the different interpretations of linear combination and how it applies to the given problem.
  • #1
mr_coffee
1,629
1
Hello everyone, I'm finishing up some matrices review and im' confused on this question i have the matrix:
-1 -3 -1 2
5 13 3 -8
3 10 9 -8
1 4 7 -4

I row reduced got this:
1 0 0 3/5
0 1 0 -4/5
0 0 1 -1/5
0 0 0 0

So you can see that this isn't a basis due to column 5 not being 0 0 0 1, but what does this mean the questions says:
If they are linearly dependent, determine a non-trivial linear relation - (a non-trivial relation is three numbers which are not all three zero.) Otherwise, if the vectors are linearly independent, enter 0's for the coefficients, since that relationship always holds.
?A + ?B + ?C + ?D = 0.
I tried 1 1 1 3/5
1 1 1 0, i tried actually 14 times, all of them are wrong hah, any help?>
 
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  • #2
Did you record the row operations that you used? Because they tell you the relationship, the reduced row of zeroes is a linear combination of the 4 rows, just recall what the combination is.
 
  • #3
I used a Ti-83 calculator to find the row reduction, he said to use them for these problems!
 
  • #4
You know how to solve a homogeneous system? If A is your matrix of column vectors, a non-trivial solution to the homogeneous system AX=0 will give you a non-trivial linear relation between your vectors.

AX is just a linear combination of the columns of A after all.

edit-are you concerned with a linear combination of the rows or the columns of your matrix? matt and i answered the different interpretations (in that order).
 
Last edited:

What is the definition of linear dependence?

Linear dependence refers to a situation in which one vector in a set of vectors can be expressed as a linear combination of the other vectors in the set.

How do you determine if a matrix has linear dependence?

To determine if a matrix has linear dependence, you can use the determinant of the matrix. If the determinant is equal to zero, then the matrix has linear dependence.

What is the purpose of solving linear dependence of a matrix?

The purpose of solving linear dependence of a matrix is to reduce the number of vectors in a set to a linearly independent set. This allows for easier calculations and analysis of the vectors.

What techniques can be used to solve for linear dependence of a matrix?

The most common technique for solving linear dependence of a matrix is to use Gaussian elimination or row reduction to transform the matrix into reduced row echelon form. Another technique is to use the Gram-Schmidt process to orthogonalize the vectors in the matrix.

How can solving linear dependence of a matrix be applied in real-world situations?

Solving linear dependence of a matrix is commonly used in fields such as engineering, physics, and computer science. It can be applied to solve systems of linear equations, analyze data sets, and determine the basis of a vector space.

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