1. The problem statement, all variables and given/known data I have an algorithm that implements Gaussian elimination. According to the text, with some modification of the indices and their in the loops, I should be able to have this algorithm perform Gauss-Jordan elimination. I also have to reduce the matrix to reduced row-echelon form, but for now I cannot figure out how I would go about modifying the indices to perform Gauss-Jordan elimination. 2. Relevant equations The input is a matrix A[1...n, 1...n] and column vector b[1...n] The output is an upper triangular matrix. Code (Text): for i←1 to n do A[i, n+1]←b[i] for i←1 to n−1 do pivot ← i for j←i+1 to n do if |A[j, i]| > |A[pivot, i]|, pivot←j for k←i to n+1 do swap(A[i, k],A[pivot, k]) for j←i+1 to n do scale←A[j, i]/A[i, i] for k←i to n+1 do A[j, k]←A[j, k]−A[i, k]∗scale 3. The attempt at a solution I have performed Gaussian Elimination on a maxtrix with 3 rows and 4 columns. This leaves a matrix with the form: Code (Text): x[SUB]1[/SUB] y[SUB]1[/SUB] z[SUB]1[/SUB] b[SUB]1[/SUB] 0 y[SUB]2[/SUB] z[SUB]2[/SUB] b[SUB]2[/SUB] 0 0 z[SUB]3[/SUB] b[SUB]3[/SUB] I understand that y1, z1, and z2 also need to be eliminated, but I can't see how to do this with the current algorithm. Could someone kindly give me a push in the right direction here?