Discovery 2.1.
Consider the following system.
(a)
Convert to an augmented matrix.
(b)
Via elementary row operations, obtain a “leading ” in the first entry of the first row (maybe swap some rows?), then use it to eliminate all other entries in the first column.
(c)
Obtain a leading in the second entry of the second row (do not use/alter the first row!), then use it to eliminate all other entries in the second column (yes, you can now alter the first row).
(d)
Obtain a leading in the third entry of the third row (do not use/alter first or second rows!), then use it to eliminate all other entries in the third column.
(e)
Turn the final augmented matrix back into a system and solve it.
Discovery 2.2.
Consider the following system.
(a)
Convert to an augmented matrix.
(b)
Via elementary row operations, obtain a leading in the first entry of the first row (maybe combine first two rows somehow?), then use it to eliminate all other entries in the first column.
(c)
Is it possible to obtain a leading in the second entry of the second row?
(d)
Obtain a leading in third entry of the second row (do not use/alter the first row!), then use it to eliminate all other entries in the third column.
(e)
Assign a parameter to every variable whose column does not contain a leading one. Turn the final augmented matrix back into a system and solve it in terms of your parameter(s).
Discovery 2.5.
In a homogeneous system, what is the relationship between the number of variables, the number of “leading ones” in the most reduced form of the coefficient matrix, and the number of parameters required to solve the system? What pattern of leading ones in a completely reduced coefficient matrix tells you that the corresponding homogeneous system has a single, unique solution?