Linear dependency matrix problem

In summary, the conversation is about a person seeking help with a question involving matrices and determinants. They discuss the use of row manipulations and the properties of determinants. The person eventually understands that they need to show linear dependency between two rows in order to prove the given condition.
  • #1
Taylor_1989
402
14

Homework Statement


Hi guys, I am having an issue understanding what to do with this question. The question is displayed below:

upload_2017-5-9_1-19-11.png


I have hand wirtten my working, as I don't now how to do matrices fully on latext.

I used the definition to get this far for part a, but not sure about the second part.
I have attche my working with what I have so far

Homework Equations

The Attempt at a Solution

 

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  • #2
You should start by thinking about properties of det(A) that you might use. Do you know anything about the effect of row manipulations on determinants?
 
  • #3
I know that is u have a triangular matrix then the det would be 0. The propble is beacuse its an arbitary matrix its throwing me off. If r2 and r1 ard linearly independent the r3 would have to = 0 which means that one of the rows could equal each other
 
  • #4
Since this is a homework problem, there must be some facts about the determinant that you can use. What formulas do you know about the determinant? What do you know about the effect of row manipulations on the determinant?
 
  • #5
I know the basic where the determniant is: ##D=a_{11}(a_{22}a_{33}-a_{23}a_{32})-a_{12}(a_{21}a_{31}-a_{23}a_{32})+a_{31}(a_{21}a_{32}-a_{22}a_{31})## I also know after reading that if you use the ro echol matrix which is done by row mainpulation then it will not effect the determinant of the matrix
 
  • #6
Taylor_1989 said:
I know the basic where the determniant is: ##D=a_{11}(a_{22}a_{33}-a_{23}a_{32})-a_{12}(a_{21}a_{31}-a_{23}a_{32})+a_{31}(a_{21}a_{32}-a_{22}a_{31})## I also know after reading that if you use the ro echol matrix which is done by row mainpulation then it will not effect the determinant of the matrix
Ok. Use the linear dependence of the first two rows to guide you in row manipulations that zero out one of them without changing the determinant. Then calculate the determinant.
 
Last edited:
  • #7
Taylor_1989 said:
I know that is u have a triangular matrix then the det would be 0. The propble is beacuse its an arbitary matrix its throwing me off. If r2 and r1 ard linearly independent the r3 would have to = 0 which means that one of the rows could equal each other

No, if you have a triangular matrix there is no reason to have zero determinant. The 3x3 identity matrix is certainly upper triangular, but has determinant = 1. Also: just because rows 1 and 2 are dependent, that would have no effect whatsoever on row 3. I don't know why you think row 3 would have to be 0. Furthermore, there is no need for any two of the rows to equal each other, as you seem to think.
 
  • #8
Ok I have finally realized what I have to do. So linear dependency means in this case you have two vectors one a scalar multiple of the other so the matrix of (1,2,3 | 2,4,6|,5,10,11) will do, to show this condition. I was under the impression I had to prove this from the question. It obvious to me that is any row in a matrix is propotional to each other would mean that the det will equal 0. Once again I thank you for your help.
 
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  • #9
Taylor_1989 said:
Ok I have finally realized what I have to do. So linear dependency means in this case you have two vectors one a scalar multiple of the other so the matrix of (1,2,3 | 2,4,6|,5,10,11) will do, to show this condition. I was under the impression I had to prove this from the question. It obvious to me that is any row in a matrix is propotional to each other would mean that the det will equal 0. Once again I thank you for your help.

Still, no. What you say is OK in part (b), but not in part (a). For example, the matrix
$$\begin{bmatrix}
2 & 0 & -1 \\ 0 & 2 & 2 \\2 & 2 & 1
\end{bmatrix}
$$
has any two rows linearly independent, but the three rows taken together are linearly dependent.
 

FAQ: Linear dependency matrix problem

1. What is a linear dependency matrix problem?

A linear dependency matrix problem is a mathematical problem that involves determining whether a set of vectors in a matrix are linearly dependent or independent. In other words, it is a way to understand the relationships between different variables in a system.

2. How do you identify a linear dependency matrix problem?

A linear dependency matrix problem can be identified by analyzing the coefficients of the variables in a system. If the coefficients can be expressed as a linear combination of each other, then the system is linearly dependent. On the other hand, if the coefficients are not dependent on each other, then the system is linearly independent.

3. What is the significance of solving a linear dependency matrix problem?

Solving a linear dependency matrix problem can help in understanding the behavior of a system, predicting future outcomes, and identifying any redundancies or inconsistencies in the data. It is also an important tool in various fields such as economics, engineering, and computer science.

4. What are some common methods for solving a linear dependency matrix problem?

There are several methods for solving a linear dependency matrix problem, including Gaussian elimination, LU decomposition, and QR decomposition. These methods involve transforming the matrix into a simpler form that is easier to analyze and solve.

5. Can a linear dependency matrix problem have multiple solutions?

Yes, a linear dependency matrix problem can have multiple solutions. In fact, there can be infinitely many solutions if the system is considered underdetermined, meaning there are more variables than equations. However, if the system is considered overdetermined, meaning there are more equations than variables, then there may be no solution or only a unique solution.

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