Solving Augmented Matrices with Gaussian Method

In summary, the conversation discusses the use of Gaussian elimination to solve a system of equations. The process involves multiplying a row by a constant and using it to eliminate a variable in another row. The Wikipedia link provided offers an explanation and example of how this method works. However, the person in the conversation found it unhelpful and questioned if the other person had actually read it.
  • #1
kash-k
17
0
|1 -5 2 |-5
|3 -14 3 |-8
|4 -18 8 |-8

above is a augmented matrix of a 3 equations. now i know that you can solve these via simul. equations however, my textbook solves them via some gaussian method but doesn't mention how it's done. it just shows -

1 -5 2 |-5
0 1 -3 |7
0 0 1 |-2

how does the textbook go from augment 1 to augment 2 using this guassian method?

thanks in advance :)
 
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  • #3
did you read it?
because i read it before i posted and let me tell you it's not helpful.
 
  • #4
Why isn't it helpful? Did you try following the example? It seems ok to me. So it goes like this:
You multiply the first row by a constant such that when it is added to the 2nd row, the left most number of the second row becomes 0. Do that to the 3rd row, then use the second row as a reference to reduce the 3rd row.
 

1. How does the Gaussian method work to solve augmented matrices?

The Gaussian method is a systematic approach to solving systems of linear equations represented by augmented matrices. It involves using a series of row operations, such as multiplication and addition, to transform the augmented matrix into a reduced row echelon form. This process simplifies the system of equations and allows for the determination of the solution.

2. What are the steps involved in using the Gaussian method to solve augmented matrices?

The steps for solving augmented matrices with the Gaussian method are:

  1. Write the augmented matrix representing the system of equations.
  2. Perform row operations to simplify the matrix, such as multiplying a row by a constant or adding a multiple of one row to another.
  3. Continue performing row operations until the matrix is in reduced row echelon form.
  4. Determine the solution by reading the values in the rightmost column of the reduced matrix.

3. What are the advantages of using the Gaussian method to solve augmented matrices?

The Gaussian method is advantageous because it is a systematic and efficient method for solving systems of linear equations. It also provides a clear and organized approach to finding the solution, making it easier to follow and understand. Furthermore, the reduced row echelon form obtained through this method allows for easy interpretation and comparison of different systems of equations.

4. Are there any limitations to using the Gaussian method for solving augmented matrices?

One limitation of the Gaussian method is that it can be time-consuming and tedious for large matrices. Additionally, this method may not work for matrices with complex or irrational coefficients. In these cases, alternative methods, such as using a calculator or computer software, may be more efficient.

5. How can the Gaussian method be applied to real-world problems?

The Gaussian method has many applications in the real world, particularly in fields such as engineering, physics, and economics. It can be used to model and solve systems of equations that represent real-world situations, such as production and demand in economics or forces acting on a structure in engineering. The method allows for the determination of the solution to these systems, which can then be used to make informed decisions or predictions.

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