Solve System of Equations via Gaussian Elimination

AI Thread Summary
The discussion centers on solving a system of equations using Gaussian elimination with an augmented matrix. The key point is that the last row of the reduced matrix does not indicate a contradiction, as it does not take the form of "0 0 0 | t" where t is non-zero. Therefore, there will always be a solution for any real values of a, b, and c. The conclusion is that regardless of the specific values of a, b, and c, solutions for the variables x, y, and z can always be found. Thus, the system of equations is consistent for any real numbers assigned to a, b, and c.
EvLer
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I am not sure how to solve this:
Given an augmented matrix, find conditions on a, b, c for which the system has solutions:
Code:
-1   -2   3    b
-1   -6   23   c
-3   2    4    a
so by Gaussian elimination, the matrix I ended up with is
Code:
1   2   -3   -b
0   4   -20  b-c
0   0   -35  (3b-a) + 2(b-c)
And now I am stuck, because there is still a variable left in the last row. Does that mean there are no such a, b, c for which the system has a solution?
Thanks in advance.
 
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EvLer said:
I am not sure how to solve this:

And now I am stuck, because there is still a variable left in the last row. Does that mean there are no such a, b, c for which the system has a solution?
Thanks in advance.

In general, when do you know there is a solution, and when do you know there is no solution?

Suppose you were given a particular a,b and c at random... would you be able to solve for x, y and z?
 
So, are you implying that the conditions I need on a, b, and c are such that
z = (3b - a + 2b - 2c)/ (-35) and so on?
The problems we have done in class were basically of the form such that the last row of coefficient part of the augm. matrix is all zeros without variables. So the conditions are only in terms of a, b, and c themselves.
 
EvLer said:
So, are you implying that the conditions I need on a, b, and c are such that
z = (3b - a + 2b - 2c)/ (-35) and so on?
The problems we have done in class were basically of the form such that the last row of coefficient part of the augm. matrix is all zeros without variables. So the conditions are only in terms of a, b, and c themselves.

The idea is that no matter what a,b,c are you can always get a solution. Like you showed above you can always solve for z, then for y then for x.

a, b and c can be any real number.

Another way to look at it is, after you reduce an augmented matrix to echelon form.. the only time you have no solution is if you have a row that is

0 0 0 | t

where t is non-zero. Any other time there is always a solution.

Since your matrix (reduced to echelon form) does not have a row like this (no matter what values a, b or c take) there is a solution for any a,b,c.

So a,b,c can be any real numbers.
 
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