Are These Row Equivalent Matrices? Why Am I Getting Different Results?

In summary: Mistakes of this nature can be prevented by verifying your work, as demonstrated here. In summary, you have not followed the proper steps to calculate the row-reduced form of the matrix.
  • #1
Pull and Twist
48
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I am having trouble with the following problem;

a.) Find a matrix B in reduced echelon form such that B is row equivalent to the given matrix A.

A=\(\displaystyle \left[\begin{array}{c}1 & 2 & 3 & -1 \\ 3 & 5 & 8 & -2 \\ 1 & 1 & 2 & 0 \end{array}\right]\)

So using my calculator I am able to get,

B=\(\displaystyle \left[\begin{array}{c}1 & 5/8 & 8/3 & -2/3 \\ 0 & 1 & 1 & -1 \\ 0 & 0 & 0 & 0 \end{array}\right]\)

The problem is that the book claims that B should be;

B=\(\displaystyle \left[\begin{array}{c}1 & 2 & 3 & -1 \\ 0 & -1 & -1 & 1 \\ 0 & 0 & 0 & 0 \end{array}\right]\)

Which is weird cause according to the row equivalency theorem, any B of A in REF should be the same unique row equivalent matrix. Why am I not getting the same result?? I am using a TI-83 Plus.
 
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  • #2
PullandTwist said:
I am having trouble with the following problem;

a.) Find a matrix B in reduced echelon form such that B is row equivalent to the given matrix A.

A=\(\displaystyle \left[\begin{array}{c}1 & 2 & 3 & -1 \\ 3 & 5 & 8 & -2 \\ 1 & 1 & 2 & 0 \end{array}\right]\)

So using my calculator I am able to get,

Unfortunately, we cannot verify your calculator input, nor the accuracy of said calculator. Sorry about that.

B=\(\displaystyle \left[\begin{array}{c}1 & 5/8 & 8/3 & -2/3 \\ 0 & 1 & 1 & -1 \\ 0 & 0 & 0 & 0 \end{array}\right]\)

The problem is that the book claims that B should be;

B=\(\displaystyle \left[\begin{array}{c}1 & 2 & 3 & -1 \\ 0 & -1 & -1 & 1 \\ 0 & 0 & 0 & 0 \end{array}\right]\)

Which is weird cause according to the row equivalency theorem, any B of A in REF should be the same unique row equivalent matrix. Why am I not getting the same result?? I am using a TI-83 Plus.

only RREF is unique, the matrix in your book appears to be properly calculated, but it is NOT in RREF, nor is your matrix $B$ (you have non-zero entries in row 1 above the leading one in row 2, as does the matrix in your book). The RREF can be found here:

Wolfram|Alpha: Computational Knowledge Engine

I verified your book's answer, using the following steps:

a) Subtract 3 times row 1 from row 2
b) Multiply row 2 by -1
c) Subtract row 1 from row 3
d) Add row 2 to row 3

Row-reduction is a path fraught with peril, simple mistakes can ruin everything.
 

FAQ: Are These Row Equivalent Matrices? Why Am I Getting Different Results?

What are row equivalent matrices?

Row equivalent matrices are matrices that can be transformed into each other by performing a sequence of elementary row operations. This means that the two matrices have the same number of rows and columns, and their corresponding entries are related by simple algebraic operations.

What are elementary row operations?

Elementary row operations are a set of three operations that can be performed on the rows of a matrix without changing the solution to a system of linear equations. These operations include: 1) multiplying a row by a nonzero constant, 2) adding a multiple of one row to another row, and 3) swapping two rows.

How do you know if two matrices are row equivalent?

Two matrices are row equivalent if one can be transformed into the other through a sequence of elementary row operations. This can be determined by performing the operations on one matrix until it is in reduced row-echelon form, and then comparing it to the other matrix. If they have the same reduced row-echelon form, then they are row equivalent.

Can row equivalent matrices have different solutions to a system of linear equations?

No, row equivalent matrices will always have the same solution to a system of linear equations. This is because the elementary row operations do not change the solution, and row equivalent matrices can be transformed into each other through a sequence of these operations.

How can row equivalent matrices be useful in solving systems of linear equations?

Row equivalent matrices can be used to simplify and solve systems of linear equations. By transforming a system of equations into an equivalent matrix, the solution can be found by performing elementary row operations and reducing the matrix to its reduced row-echelon form. This can help to easily identify the solution to the system of equations.

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