00:01
So you can apply row operations to convert every m by n matrix to a reduced echelon form.
00:35
Furthermore, there is one and only one reduced echelon form for each matrix.
01:13
The operations predate gauss and jordan, whose names are associated with them.
01:18
They were used by ancient chinese to solve simultaneous linear equations, and were probably discovered independently at various times and places, as they are pretty intuitive.
01:30
There are three elementary row operations.
01:45
First, there's exchange two rows, then multiply or divide a row by a non -zero constant, and third or lastly, adding or subtracting a multiple of one row from another.
02:43
If the rows of a matrix are the coefficients in a linear equation, these three operations correspond to exchanging equations, multiplying or dividing an equation by a non -zero constant, and adding or subtracting a multiple of one equation from another.
03:02
None of these operations change the set of solutions of a system of linear equations.
03:08
So you can perform these operations at any order you like...