Applying Gaussian Elimination to a Matrix - Understanding the Correct Method

In summary, the conversation discusses Gaussian elimination on a matrix and the attempt at using a different method to solve it. The expert suggests that while the method is not illegal, it may not be the most efficient and recommends a simpler approach. The conversation ends with the understanding that the original method was incorrect and the expert provides the correct solution.
  • #1
robertjford80
388
0

Homework Statement



Apply Gaussian elimination to the following matrix

2 -3 0 3
4 -5 1 7
2 -1 -3 5

I understand how to get the answer.

The Attempt at a Solution



My question is why doesn't the following method work: Switch Z over into the first column, move row 1 to row 3, then exchange rows 1 and 2 so that the new matrix is
1 -5 4 7
-3 -1 2 5
0 -3 2 3

Multiply the first row by 3 and add that to equation 2 to get:

1 -5 4 7
0 5 8 35
0 -3 2 3

Multiply row 2 by 3/5 and add that to equation 3 to get

1 -5 4 7
0 5 8 35
0 0 (34/5) 24

By this time I realized I was on the wrong track but I don't why what I did was illegal.
 
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  • #2
robertjford80 said:

Homework Statement



Apply Gaussian elimination to the following matrix

2 -3 0 3
4 -5 1 7
2 -1 -3 5

I understand how to get the answer.




The Attempt at a Solution



My question is why doesn't the following method work: Switch Z over into the first column, move row 1 to row 3, then exchange rows 1 and 2 so that the new matrix is
1 -5 4 7
-3 -1 2 5
0 -3 2 3
The 3rd row has a sign error.
robertjford80 said:
Multiply the first row by 3 and add that to equation 2 to get:

1 -5 4 7
0 5 8 35
0 -3 2 3
And you have some more error in the matrix above.
robertjford80 said:
Multiply row 2 by 3/5 and add that to equation 3 to get

1 -5 4 7
0 5 8 35
0 0 (34/5) 24

By this time I realized I was on the wrong track but I don't why what I did was illegal.
No, it's not illegal, but that's not to say it's a good idea.

The solution to the system that your augmented matrix represents is x = 3, y = 1, z = 0. If you switch columns you are in essence swapping variables.

When I did what you described, I quit at this matrix:
1 -5 4 | 7
0 8 -7 | -13
0 3 -2 | -3

I didn't bother to continue reducing it. Instead I checked that x = 0, y = 1, z = 3 was the solution, which it was.

BTW, you did an awful lot of extra work swapping columns and rows that you didn't really need to do. It's much easier to use the original row-1, col-1 number to eliminate the two entries under it, then use the row-2, col-2 entry to eliminate the entries above and below it. You quickly get to the solution this way.
 
  • #3
Good, thanks.
 

Related to Applying Gaussian Elimination to a Matrix - Understanding the Correct Method

What is Gaussian Elimination?

Gaussian Elimination is a method used to solve systems of linear equations by performing a series of operations on a matrix to transform it into an upper triangular matrix. This process helps to simplify and solve complex systems of equations.

What is the correct method for applying Gaussian Elimination?

The correct method for applying Gaussian Elimination involves performing row operations on a matrix to reduce it to its upper triangular form. This includes operations such as swapping rows, multiplying rows by a constant, and adding or subtracting rows from each other.

Why is Gaussian Elimination useful?

Gaussian Elimination is useful because it provides a systematic way to solve systems of linear equations. It allows for efficient and accurate solutions to complex problems in various fields such as science, engineering, and economics.

What are the limitations of Gaussian Elimination?

One limitation of Gaussian Elimination is that it can only be applied to linear equations. It also becomes computationally expensive for larger matrices and systems with many variables. In some cases, the method may also produce round-off errors.

How is Gaussian Elimination related to other mathematical concepts?

Gaussian Elimination is related to other mathematical concepts such as matrix operations, linear algebra, and systems of equations. It is also the basis for other techniques such as LU decomposition and matrix inversion.

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