Exercises — Pivot positions, free variables
Before we begin, three words we lean on constantly, restated so nothing is assumed:
If any of those still feel wobbly, reread Pivot positions, free variables first — this page trains on top of it.
Level 1 — Recognition
Goal: just look at a reduced matrix and read off pivots, ranks, and free counts. No arithmetic beyond counting.
Exercise 1.1
The matrix below is already in reduced row echelon form (RREF). List its pivot columns, its rank , and — if these were the coefficients of a system in variables — its free variables.
Recall Solution 1.1
WHAT to look for: the first nonzero entry of each nonzero row — each is a leading 1, and each sits in its own column. Row 1's leading 1 is in column 1. Row 2's is in column 2. Row 3's is in column 4.
- Pivot columns: .
- Rank (three pivots).
- Column 3 has no leading 1 → is the only free variable.
- Check: . ✓
Exercise 1.2
For each RREF, give , , and .
Recall Solution 1.2
- : columns, one leading 1 (row 1, col 1) so . .
- : , three leading 1's on the diagonal so . .
- : , leading 1's in columns 1 and 2 so ; column 3 is free. .
Level 2 — Application
Goal: do the row reduction yourself, then read off pivots and write the solution set.
Exercise 2.1
Solve, and state the number of free variables:
Recall Solution 2.1
Step 1 — clear below the first pivot. : Why? We want zeros under the leading 1 in column 1 so the echelon staircase appears. Step 2 — normalise the second pivot. : gives . Pivots sit in columns 1 and 3; column 2 has none → is free (, , so ). Step 3 — back-substitute. Row 1: . With : One free variable ⇒ a line in 3D. ✓ (See Null Space and Solution Sets of Ax=0 for why the second vector is the null-space direction.)
Exercise 2.2
Solve:
Recall Solution 2.2
Step 1 — get a leading 1. Swap rows so the tidy row is on top, : Step 2 — clear below. : . Step 3 — normalise. . Both columns are pivot columns → no free variables (). Step 4 — back-substitute. . Unique solution . ✓
Level 3 — Analysis
Goal: reason about pivots without fully solving — deduce shape, consistency, and counts.
Exercise 3.1
A system has of size and, after reduction, . Assuming the system is consistent, what is the dimension of the solution set, and what geometric object is it?
Recall Solution 3.1
variables, pivots. . A consistent system with 3 free variables has a 3-dimensional flat (a "3-plane") of solutions. (This is exactly of the shifted null space; see Rank and the Rank-Nullity Theorem.)
Exercise 3.2
An augmented matrix reduces to
For each, say whether it's consistent, how many free variables (if any), and the solution set's shape.
Recall Solution 3.2
Left matrix. The last row is all zeros — a harmless , not a pivot in the augmented column. So it's consistent. Coefficient pivots sit in columns 1 and 3; column 2 is free ⇒ . Solution set is a line. Writing : , , so . Right matrix. Bottom row reads — the augmented column is a pivot column. Inconsistent → no solution. Free-variable count is irrelevant here: freedom describes a solution set only when one exists.
Exercise 3.3
An system has that is with . Is a solution guaranteed to exist, and if so is it unique? Justify with pivots.
Recall Solution 3.3
, so every column of is a pivot column → no free variables. Because has a pivot in every row too (), the augmented column can never become a pivot column (there's no all-zero coefficient row to sit above a nonzero right side). So the system is consistent for every , and with free variables the solution is unique — exactly one point. (This is the invertible case; see Existence and Uniqueness of Solutions.)
Level 4 — Synthesis
Goal: build matrices/systems that meet a spec — reverse-engineering the pivot rules.
Exercise 4.1
Construct a matrix (coefficients only) whose homogeneous system has a solution set that is a plane (2-dimensional). Verify your and free count.
Recall Solution 4.1
A plane = free variables. With , we need , so . Build any RREF with exactly two leading 1's, e.g. Pivots in columns 1, 2 → . Columns 3, 4 free → . A homogeneous system is always consistent ( works), so the solution set is a genuine 2-plane through the origin. ✓ (Its two spanning directions form a basis of the null space — see Basis and Dimension.)
Exercise 4.2
Find a value of that makes the columns of
linearly dependent, and one value that keeps them independent. Express your reasoning through pivots.
Recall Solution 4.2
Columns are independent every column is a pivot column (no free variables in ; see Linear Independence). Reduce: gives .
- If (e.g. ): second pivot exists, → independent.
- If , i.e. : second row is zero, only , column 2 is free → dependent. Answer: makes them dependent; (any ) keeps them independent.
Exercise 4.3
Design a system with of size that is inconsistent. Show the offending pivot.
Recall Solution 4.3
Make the two coefficient rows proportional but the right-hand sides not matching. E.g. The bottom row is : the augmented column earns a pivot, so the system is inconsistent. ✓
Level 5 — Mastery
Goal: chain reduction, pivots, consistency, and geometry into one multi-part problem.
Exercise 5.1
Consider the parametrised augmented system
(a) Row-reduce (leave symbolic). (b) For which is the system consistent? (c) For that/those , give the pivot columns, the number of free variables, and the full solution set. (d) Name the geometric shape.
Recall Solution 5.1
(a) Reduce. and : Now : (b) Consistency. The bottom row reads . This is a true statement (no augmented pivot) exactly when , i.e. . For any the augmented column takes a pivot → inconsistent. (c) At . Coefficient pivots sit in columns 1 and 3; column 2 is free (, , ). Back-substitute with : row 2 gives ; row 1 gives . So (d) Shape. One free variable ⇒ a line in 3D, passing through in the direction .
Exercise 5.2
Same coefficient matrix as 5.1, but now the homogeneous version . Without redoing all the work, state its solution set and explain the relationship to 5.1's answer using pivots.
Recall Solution 5.2
The coefficient reduction is identical, giving pivots in columns 1, 3 and free column 2 — so regardless of the right-hand side (pivots depend only on ). Setting the constants to zero: , , : This is the line through the origin in the same direction . The inhomogeneous solution set from 5.1 is this line shifted by the particular point — geometrically, two parallel lines. That "particular + null-space" split is the general structure of solution sets (Null Space and Solution Sets of Ax=0).

Recall One-line self-check for the whole page
Free variables count non-pivot columns (), the right-hand side controls only consistency, and pivot positions belong to alone. Give the master formula and the two independent questions it splits into ::: ; Question 1 (existence) depends on /consistency, Question 2 (size of solution set) depends only on 's pivots.
Connections
- Pivot positions, free variables — the parent this page drills.
- Row Reduction and Echelon Forms
- Rank and the Rank-Nullity Theorem
- Null Space and Solution Sets of Ax=0
- Linear Independence
- Existence and Uniqueness of Solutions
- Basis and Dimension