Reduced a big matrix, now the parametric form is not right, :\

In summary, the conversation discusses a problem involving a matrix and its row reduced form. The correct solution is provided, along with a discussion on choosing variables and putting the solution in vectorial notation. There is also a minor error in the solution that is pointed out and corrected.
  • #1
mr_coffee
1,629
1
Hello everyone I did the following problem:
Click http://img220.imageshack.us/img220/8486/untitled1copy4oq.jpg to view the problem and my answer.

The row reduced form is:
1 5 0 0 -7 6 -7
0 0 1 0 -1 1 -1
0 0 0 1 - 2 -4 8

Any help would be great
 
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  • #2
Your matrix seems to be correct, and is:

[tex]\left( {\begin{array}{*{20}c}
1 & 5 & 0 & 0 & { - 7} & 6 &\vline & { - 7} \\
0 & 0 & 1 & 0 & { - 1} & 1 &\vline & { - 1} \\
0 & 0 & 0 & 1 & { - 2} & { - 4} &\vline & 8 \\

\end{array} } \right)[/tex]

Now we have 3 lineair indepedant equations with 6 variables which means we can 'choose' 3 variables. We keep the variables [tex]x_1[/tex], [tex]x_3[/tex] and [tex]x_4[/tex]. Let [tex]x_2 = s[/tex], [tex]x_5 = t[/tex] and [tex]x_6 = u[/tex].

This gives the solution of the system:

[tex]\left\{ \begin{gathered}
x_1 + 5s - 7t + 6u = - 7 \hfill \\
x_3 - t + u = - 1 \hfill \\
x_4 - 2t - 4u = 8 \hfill \\
\end{gathered} \right. \Leftrightarrow \left\{ \begin{gathered}
x_1 = - 7 - 5s + 7t - 6u \hfill \\
x_3 = - 1 + t - u \hfill \\
x_4 = 8 + 2t + 4u \hfill \\
\end{gathered} \right[/tex]

Can you put it in vectorial notation now?
 
  • #3
hm...i don't see how 'im still missing this:
i entered in:
-7 -5 7 6
0 1 0 0
-1 0 1 -1
8 0 0 4
0 0 1 0
0 0 0 1

still wrong, thanks for the reply!
 
  • #4
I think you for got the 2 in column 3 for [itex]x_4[/itex] since that has "2t) in its solution.
 
  • #5
I'm stilling screwing somthing up...I fixed what you said, but still not the right answer, and I know its row reduced correctly because I checked it with my calculator! here is the picture of what I wrote and submitted:
http://img214.imageshack.us/img214/8780/gfsdgfd6wq.jpg Thanks for the help!
 
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  • #6
I see you entered "6" in the last column for [itex]x_1[/itex] and I think that has to be "-6" (check my last system).
 
  • #7
ah ha! my bad! thanks for the help! :biggrin:
 
  • #8
It was correct now? Glad I could help :smile:
 

1. What does it mean to "reduce" a matrix?

Reducing a matrix refers to the process of transforming it into a simpler form, typically by using elementary row operations, such as adding rows together or multiplying rows by a scalar value. The resulting reduced matrix will have the same solutions as the original matrix, but it may be easier to work with or solve.

2. How does reducing a matrix affect its parametric form?

Reducing a matrix can change its parametric form by altering the values of the parameters or the number of parameters needed to describe the solutions. This is because the reduced form of a matrix is typically simpler and more organized, so the parametric form may need to be adjusted accordingly.

3. Why might the parametric form be incorrect after reducing a matrix?

There are a few reasons why the parametric form may not be correct after reducing a matrix. One possibility is that errors were made during the reduction process. Another possibility is that the original matrix was not in the correct form to begin with, so the resulting parametric form is also incorrect.

4. How can I determine if the parametric form is correct after reducing a matrix?

The best way to determine if the parametric form is correct after reducing a matrix is to check it against the original matrix and see if they have the same solutions. You can also try plugging in different values for the parameters and checking if they satisfy the original matrix.

5. Can the parametric form always be reduced to a simpler form?

In general, yes, the parametric form can be reduced to a simpler form. However, there may be cases where the parametric form cannot be further simplified, or where reducing it would not be helpful in solving the original matrix. It ultimately depends on the specific matrix and its solutions.

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