Reducing a matrix to echelon form

In summary, the conversation is about reducing a matrix to echelon form and finding the ranks and solution in vector form for different values of a variable. The individual has run into a problem with two leading zeroes in the last three rows and is unsure about the ranks and solution in vector form. They are seeking help and clarification on these topics.
  • #1
Mohamed Abdul

Homework Statement


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(i) Reduce the system to echelon form C|d
(ii) For k = -12, what are the ranks of C and C|d? Find the solution in vector form if the system is consistent.
(iii) Repeat part (b) above for k = −18

Homework Equations



Gaussian elimination I used here:
http://mathworld.wolfram.com/GaussianElimination.html

The Attempt at a Solution


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[/B]

I've attempted reducing the matrix but have run into this problem where I have two zeroes leading in the last three rows. I don't know what I am doing wrong, so any help would be greatly appreciated.

I can't continue with either parts b or c without solving part a, and I'm not too sure about those parts either.
 

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  • #2
Mohamed Abdul said:
I've attempted reducing the matrix but have run into this problem where I have two zeroes leading in the last three rows. I don't know what I am doing wrong, so any help would be greatly appreciated.
Your algebra looks ok. Having these zeros does not necessarily mean its wrong, and it is probably the reason that the problem is asking for the rank of the matrix in part ii.
 
  • #3
NFuller said:
Your algebra looks ok. Having these zeros does not necessarily mean its wrong, and it is probably the reason that the problem is asking for the rank of the matrix in part ii.
Alright, I understand. However, how would the ranks change regardless of my k value considering that the ranks only depend on the C part of C|d. Also, when it says to find the solution in vector form, does that mean I just write down the last column when I plug in k?
 
  • #4
Mohamed Abdul said:
However, how would the ranks change regardless of my k value considering that the ranks only depend on the C part of C|d.
The rank of ##C## will not change. I am not completely sure what the question means when it asks for the rank of ##C|d##.
Mohamed Abdul said:
when it says to find the solution in vector form, does that mean I just write down the last column when I plug in k?
You can write the solution vector as the last column ##d## if you get the augmented matrix into reduced echelon form. Otherwise, you can perform Gaussian elimination to find the solution.
 

What is the purpose of reducing a matrix to echelon form?

The purpose of reducing a matrix to echelon form is to simplify the matrix and make it easier to perform calculations on it. It also helps in solving systems of linear equations and finding the rank of a matrix.

What is the process of reducing a matrix to echelon form?

The process of reducing a matrix to echelon form involves performing a series of elementary row operations on the matrix. These operations include multiplying a row by a non-zero constant, swapping two rows, and adding a multiple of one row to another row.

What is the difference between echelon form and reduced echelon form?

Echelon form is a partially reduced form of a matrix where all non-zero rows are above any rows of all zeroes, and the leading coefficient of each row is to the right of the leading coefficient of the row above it. Reduced echelon form is the fully reduced form of a matrix where all leading coefficients are one and all other entries in the same column are zero.

How can reducing a matrix to echelon form help in solving systems of equations?

Reducing a matrix to echelon form can help in solving systems of equations by making it easier to identify and solve for the unknown variables. The reduced echelon form of a matrix represents the solutions to the system of equations in a simple and organized form.

Can any matrix be reduced to echelon form?

Yes, any matrix can be reduced to echelon form. However, the process of reducing a matrix to echelon form may not always result in a unique solution or a reduced echelon form. This can happen if the matrix is singular or if the leading coefficients of the rows do not have a common factor of one.

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