4.5.10 · D1Linear Algebra (Full)

Foundations — Row echelon form and reduced row echelon form

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This page assumes you have seen none of the notation in the parent note. We build every symbol from the ground up, in an order where each idea leans only on the ones before it.


0. What is a linear equation? (the atom)

Before matrices, before staircases, there is the linear equation.

An equation like is a promise: whatever numbers we finally put in the boxes, the left side must total the right side. The word linear means every box appears alone (to the power ) — never , never , never .

Figure — Row echelon form and reduced row echelon form

1. A system: many promises at once

The curly brace { means "all of these together". Geometrically each equation is a flat sheet in space; a solution is a point sitting on all the sheets at once — an intersection. See Solving Systems of Linear Equations.


2. From equations to a grid of numbers — the matrix

Take the system above. Line up the coefficients by column — all the -numbers in column 1, all the -numbers in column 2, all the -numbers in column 3:

Nothing was thrown away except the box-names, and we agreed on their order (x, y, z). The numbers are the equations now.


3. The augmented matrix — keeping the right-hand side

The equations also have constants after the sign (). We tack them on as one extra column, drawn after a vertical bar to remember "these were the answers, not coefficients".

Figure — Row echelon form and reduced row echelon form

4. Moves that don't lie — elementary row operations

We now want to simplify the grid without changing which box-values solve it. Only three moves are allowed, and each is chosen because it is reversible (you can undo it), which is exactly why it cannot lose or invent a solution.

Why "add a multiple of one row" is safe: adding equal amounts to both sides of a true equation keeps it true, and you can subtract the same amount to reverse it. Each of these three moves corresponds to left-multiplying by an elementary matrix — but you don't need that yet.

Figure — Row echelon form and reduced row echelon form

5. The pivot — the first real number in a row

Now the star of the show.

A zero row (all s) has no pivot — it makes no promise at all ().


6. The staircase — Row Echelon Form (REF)

Condition 2 is the "down-and-right" staircase; condition 3 is what isolates variables. Reaching REF is exactly Gaussian Elimination.

Figure — Row echelon form and reduced row echelon form

7. Dusting the steps — Reduced Row Echelon Form (RREF)

Reaching this is Gauss-Jordan Elimination. The payoff: each pivot row reads directly as "variable number", no climbing required. Crucial fact: RREF is unique for a given matrix, while REF is not (many staircases, one dusted form).


8. Reading the finished grid — three outcomes

Once in REF/RREF, count pivots. The number of pivots is the rank.

  • One solution: a pivot in every variable column, none in the constants column.
  • No solution (inconsistent): a pivot in the constants column — a row saying . See Solving Systems of Linear Equations.
  • Infinitely many: some variable column has no pivot → that variable is a free variable, free to be anything, and everything else follows.

Prerequisite map

Variables and coefficients

Linear equation = straight line

System of equations

Matrix grid of numbers

Augmented matrix

Elementary row operations

Pivot leading entry

Row Echelon Form

Reduced Row Echelon Form

Read off solutions rank freedom


Equipment checklist

What does the word "linear" force each variable to look like in an equation?
It appears alone, to the first power only — no squares, no products, no roots — so the graph is a straight line.
What is a coefficient versus a variable?
A coefficient is a known number multiplying a variable; a variable is the unknown box we solve for.
What does mean?
Row number of the matrix, counting from the top.
Why is the last column of an augmented matrix drawn after a bar?
It holds the constants (right-hand sides), not a variable's coefficients — read differently.
Name the three elementary row operations.
Swap two rows; scale a row by a non-zero constant; add a multiple of one row to another.
Why must the scale constant be non-zero?
Scaling by erases the equation and cannot be undone — it is irreversible, so it could lose solutions.
Why do all three operations preserve the solution set?
Each one is reversible, so no solution can be gained or lost.
What is a pivot?
The first non-zero entry (reading left to right) in a non-zero row.
Does a zero row have a pivot?
No — an all-zero row makes no promise and contributes no pivot.
What shape do the pivots trace in REF?
A staircase stepping only right and down, with zeros below each pivot.
Two extra conditions RREF adds beyond REF?
Every pivot equals 1, and each pivot is the only non-zero entry in its column.
Which form is unique — REF or RREF?
Only RREF is unique for a given matrix.
What does a pivot in the constants column mean?
The system is inconsistent — a row reads 0 = nonzero — so no solution.
What is a free variable?
A variable whose column has no pivot; it can take any value.

Connections