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The matrix \( A \) has been reduced to its reduced row-echelon form (RREF). The result is:

\[
\text{RREF}(A) = \begin{pmatrix}
1 & 0 & 0 & -2 \\
0 & 1 & 0 & 2 \\
0 & 0 & 1 & -4
\end{pmatrix}
\]

The pivot columns are \( [0, 1, 2] \), indicating that each of these columns contains leading 1's in the final form.

Would you like further details on the steps to achieve this or any other explanations?

Here are some related questions:
1. What are the properties of matrices in reduced row-echelon form?
2. How do elementary row operations affect a matrix?
3. What is the significance of pivot columns in the context of linear algebra?
4. How can reduced row-echelon form help in solving systems of linear equations?
5. How does Gaussian elimination relate to reduced row-echelon form?

**Tip:** When reducing matrices, focusing on eliminating one variable at a time using row operations simplifies the process.

Reduce the matrix A = [[3, 3, -2, 8], [-1, -3, 2, -12], [2, -1, -2, 2]] to reduced row-echelon form.

Step-by-step solution for reducing the matrix A = [[3, 3, -2, 8], [-1, -3, 2, -12], [2, -1, -2, 2]] to reduced row-echelon form using elementary row operations. This solution includes key concepts from linear algebra, such as matrix operations and Gauss-Jordan elimination, ideal for college students studying linear algebra.

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