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Math · Linear Algebra

Chapter 2: Systems of Linear Equations

Gaussian Elimination

Clear out entries until the answer is obvious.

Lesson
2
Time
About 24 minutes
0 of 12 done

Step 1: Let's Learn

Read it, or press Listen and follow the words.

The goal is a staircase of zeros below the diagonal. Once the matrix has that shape, the last equation has one unknown and the rest unravel.

Pivots

A pivot is the first non-zero entry in a row. Each pivot is used to clear everything beneath it.

Clearing a column

Subtract the right multiple of the pivot row from each row below. The chosen multiple is whatever makes that entry zero.

Back substitution

Solve the bottom equation, substitute upward, and repeat. Each step has exactly one new unknown.

Going further

Clearing above the pivots too, and scaling each pivot to 1, gives reduced row echelon form. The answers then sit in the last column.

Why it is the standard method

Elimination is systematic and never gets stuck. It is what a computer does, on systems with thousands of unknowns.

Clear entries until the answer is visible

Elimination drives the matrix towards row echelon form, where each row starts further right than the one above. In that form the last equation involves one unknown and back-substitution finishes it.

Pivots are the leading entries

The first nonzero entry in each row is a pivot, and its column is a pivot column. Counting pivots is how the number of solutions and the rank are read off, so identifying them matters.

Reduced row echelon form

Continuing until each pivot is 1 with zeros above and below gives the reduced form, in which the solution can be read directly with no back-substitution. It is unique for a given matrix.

It is a genuine algorithm

Elimination terminates in a predictable number of steps regardless of the matrix. That is why it is what computers actually run, and why solving large systems is a routine rather than an art.

Step 2: Try It Yourself

Tap and try it out.

Row reduce this by hand and then set the entries to match your result. A zero below the first pivot means the column is cleared.
xy=1273111

Step 3: Watch an Example

One step at a time.

Watch Sofia Eliminate

Sofia reduces the rows [1, 2 | 7] and [3, 1 | 11].

  1. Step 1

    She uses the leading 1 in row 1 as the pivot.

Step 4: Your Turn

Practice makes it stick.

The Bottom Row

Problem 1 of 2

A reduced row reads [0, 4 | 12]. What is y?

The Substitution

Problem 2 of 2

Row 1 reads [1, 2 | 7] and you know y = 2. What is x?

Reduce and Solve

1 of 8

A row reads [0, 3 | 9]. What is y?

2 of 8

A row reads [0, −2 | 8]. What is y?

3 of 8

Row 1 is [1, 1 | 10] and y = 4. What is x?

4 of 8

Clearing the entry 5 below a pivot of 1. What multiple of the pivot row is subtracted?

5 of 8

In reduced row echelon form, what is every pivot scaled to?

6 of 8

A 3 by 3 system fully reduced. How many pivots does it have if it has a unique solution?

7 of 8

Order the steps of Gaussian elimination.

  1. 1Clear every entry beneath that pivot
  2. 2Move to the next column and repeat
  3. 3Back-substitute from the bottom row upward
  4. 4Choose a pivot in the first column

8 of 8

A row reads [0, 1 | −6]. What is y?

Step 5: Quick Check

Show what you know.

Question 1 of 2

A row reads [0, 5 | 20]. What is y?

Question 2 of 2

What shape is Gaussian elimination aiming for?

What You Learned

  • Elimination clears entries below each pivot until the matrix is a staircase.
  • The bottom row then has one unknown, and back substitution unravels the rest.
  • Reduced row echelon form goes further and leaves the answers in the last column.