From a8c06d21c5613b4d61ac9186ea8fb98b1b946944 Mon Sep 17 00:00:00 2001
From: Steven Clontz
Date: Wed, 25 Feb 2026 19:04:53 +0000
Subject: [PATCH 1/2] Recharacterize EV4 for arbitrary vectors (not just zero
vector).
---
source/linear-algebra/source/02-EV/04.ptx | 280 +++++++++++++++-------
1 file changed, 188 insertions(+), 92 deletions(-)
diff --git a/source/linear-algebra/source/02-EV/04.ptx b/source/linear-algebra/source/02-EV/04.ptx
index b4c37ceda..0850aeb2f 100644
--- a/source/linear-algebra/source/02-EV/04.ptx
+++ b/source/linear-algebra/source/02-EV/04.ptx
@@ -162,137 +162,216 @@
- Let \vec w = 3\vec v_1 - \vec v_2 - 5 \vec v_3 = \left[\begin{array}{c}\unknown \\ \unknown \\ \unknown\end{array}\right].
- The set \{\vec v_1,\vec v_2,\vec v_3,\vec w\} is...
+ To solve the vector equation x_1\vec v_1 + x_2\vec v_2 = \vec v_3 , we could calculate
+\RREF\left[\begin{array}{cc|c}
+-2 & 1 & -2 \\
+0 & 3 & 0 \\
+-2 & 5 & 4
+\end{array}\right]=
+\left[\begin{array}{cc|c}
+1 & 0 & 0 \\
+0 & 1 & 0 \\
+0 & 0 & 1
+\end{array}\right]
+ .
+ What can we conclude?
- linearly dependent: at least one vector is a linear combination of others
- linearly independent: no vector is a linear combination of others
+ The equation is consistent, so \vec v_3 is a linear combination of \vec v_1,\vec v_2
+ The equation is consistent, so \vec v_3 is not a linear combination of \vec v_1,\vec v_2
+ The equation has no solutions, so \vec v_3 is a linear combination of \vec v_1,\vec v_2
+ The equation has no solutions, so \vec v_3 is not a linear combination of \vec v_1,\vec v_2
- A.
+ D.
-\vec w is a linear combination of the others, so the set is dependent.
+The third row requires 0=1, a contradiction. Thus the equation has no
+solutions, which means there is no linear combination of \vec v_1,\vec v_2
+which equals \vec v_3
-
+
- Find \RREF \left[\begin{array}{ccc|c}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w \\
- \end{array}\right]=
- \RREF \left[\begin{array}{ccc|c}
- -2 & 1 &-2 & \unknown \\
- 0 & 3 & 5 & \unknown \\
- 0 &0 &4 & \unknown
- \end{array}\right]= \unknown .
+ We can similarly show \vec v_2 is not a linear combination of
+ \vec v_1,\vec v_3, and \vec v_3 is not a linear combination
+ of \vec v_1,\vec v_2.
+ Therefore, the set \{\vec v_1,\vec v_2,\vec v_3\} is linearly...
+
+
+ independent, because one of the vectors cannot be written as a
+ linear combination of the others.
+
+ independent, because none of the vectors can be written as a
+ linear combination of the others.
+
+ dependent, because one of the vectors can be written as a
+ linear combination of the others.
+
+ dependent, because every vector can be written as a
+ linear combination of the others.
+
-
- What does this tell you about solution set for the vector equation
- x_1\vec{v}_1+x_2\vec{v}_2+x_3\vec{v}_3 =\vec w?
+
+
+ D.
+
+The third row requires 0=1, a contradiction. Thus the equation has no
+solutions, which means there is no linear combination of \vec v_1,\vec v_2
+which equals \vec v_3
+
+
+
+
+
+
+ Let \vec w = 3\vec v_1 - \vec v_2 - 2 \vec v_3 = \left[\begin{array}{c}-3 \\ -13 \\ -8 \end{array}\right].
+ The set \{\vec v_1,\vec v_2,\vec v_3,\vec w\} is linearly...
- -
-
- It is inconsistent.
-
-
- -
-
- It is consistent with one solution.
-
-
- -
-
- It is consistent with infinitely many solutions.
-
-
+
+ independent, because one of the vectors cannot be written as a
+ linear combination of the others.
+
+ independent, because none of the vectors can be written as a
+ linear combination of the others.
+
+ dependent, because one of the vectors can be written as a
+ linear combination of the others.
+
+ dependent, because every vector can be written as a
+ linear combination of the others.
- B.
- Each variable is set equal to a specific value.
+ A.
+
+\vec w is a linear combination of the others, so the set is dependent.
+
- Find \RREF \left[\begin{array}{cccc|c}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w & \vec 0\\
- \end{array}\right]=
+ To decide whether \{\vec v_1,\vec v_2,\vec v_3,\vec v_4\} spans
+ \mathbb R^4, we would consider how to solve the vector equation x_1\vec v_1 + x_2\vec v_2 +x_3 \vec v_3+x_4\vec w= \left[\begin{array}{c}\unknown\\\unknown\\\unknown\end{array}\right] for some arbitrary vector \left[\begin{array}{c}\unknown\\\unknown\\\unknown\end{array}\right]:
\RREF \left[\begin{array}{cccc|c}
- -2 & 1 &-2 & \unknown & 0\\
- 0 & 3 & 5 & \unknown & 0 \\
- 0 &0 &4 & \unknown & 0
- \end{array}\right]= \unknown .
+ -2 & 1 &-2 & -3 & \unknown \\
+ 0 & 3 & 5 & -13 & \unknown \\
+ 0 &0 &4 & -8 & \unknown
+ \end{array}\right]=
+ \left[\begin{array}{cccc|c}
+ 1 & 0 &0 & 3 & \unknown \\
+ 0 & 1 & 0 & -1 & \unknown \\
+ 0 &0 &1 & 2 & \unknown
+ \end{array}\right] .
- What does this tell you about solution set for the vector equation
- x_1\vec{v}_1+x_2\vec{v}_2+x_3\vec{v}_3 + x_4\vec w=\vec{0}?
+ What does this tell you about solution set for the vector equation?
-
- It is inconsistent.
+ It is inconsistent, so the set does not span \mathbb R^4.
-
- It is consistent with one solution.
+ It is consistent with one solution, so the set spans \mathbb R^4.
-
- It is consistent with infinitely many solutions.
+ It is consistent with infinitely many solutions, so the
+ set spans \mathbb R^4.
-
+
C.
- \vec w's column is not a pivot, revealing a free variable and infinitely-many solutions.
+ The non-pivot column guarantees a free variable which could equal
+ any real number.
-
+
+
+
+
+We can also use this same equation to explain why
+\{\vec v_1,\vec v_2,\vec v_3,\vec w\}
+is linearly dependent! The RREF matrix guarantees that \vec w is
+a linear combination of the other vectors because it guarantees the matrix
+will have...
+
+ -
+
+a pivot row
+
+
+ -
+
+a non-pivot row
+
+
+ -
+
+a pivot column
+
+
+ -
+
+a non-pivot column
+
+
+
+
+
+
+ D.
+
+When we rewrite the matrix like so:
+ \RREF \left[\begin{array}{ccc|c}
+ -2 & 1 &-2 & -3 \\
+ 0 & 3 & 5 & -13 \\
+ 0 &0 &4 & -8
+ \end{array}\right]=
+ \left[\begin{array}{ccc|c}
+ 1 & 0 &0 & 3 \\
+ 0 & 1 & 0 & -1 \\
+ 0 &0 &1 & 2
+ \end{array}\right]
+we see that a non-pivot column demonstrates how to construct
+its vector as a linear combination of the others.
+
+
+
-It follows that \{\vec v_1,\vec v_2,\vec v_3,\vec w\}
-is linearly dependent because x_1\vec{v}_1+x_2\vec{v}_2+x_3\vec{v}_3 + x_4\vec w=\vec{0}
-had the number of solutions you found in the previous task.
-Which feature of which RREF matrix best reveals this?
+Now, if all we knew was that the RREF matrix for the equation
+ x_1\vec v_1 + x_2\vec v_2 +x_3 \vec v_3+x_4\vec w= \left[\begin{array}{c}\unknown\\\unknown\\\unknown\end{array}\right]
+had this one feature, then we would know this about its solutions:
-
-The pivot column in the augmented matrix
-\RREF \left[\begin{array}{ccc|c}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w
-\end{array}\right].
+It must have a unique solution.
-
-The pivot column in the coefficient matrix
-\RREF \left[\begin{array}{cccc}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w
-\end{array}\right].
+It must have infinitely-many solutions.
-
-The non-pivot column in the augmented matrix
-\RREF \left[\begin{array}{ccc|c}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w
-\end{array}\right].
+It's possible for a solution to the equation to be unique.
-
-The non-pivot column in the coefficient matrix
-\RREF \left[\begin{array}{cccc}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w
-\end{array}\right].
+It's impossible for a solution to the equation to be unique.
@@ -301,18 +380,37 @@ The non-pivot column in the coefficient matrix
D.
-\RREF \left[\begin{array}{cccc}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w
-\end{array}\right] (or \RREF \left[\begin{array}{cccc|c}
- \vec v_1 & \vec v_2 & \vec v_3 & \vec w & \vec 0
-\end{array}\right]) can be used to solve
-x_1\vec{v}_1+x_2\vec{v}_2+x_3\vec{v}_3 + x_4\vec w=\vec{0},
-and the non-pivot column reveals it has infinitely-many solutions.
+The free variable guarantees that, as long as there are no contradictions,
+solutions are not unique.
+
+
+
+
+
+How would this change if \left[\begin{array}{c}\unknown\\\unknown\\\unknown\end{array}\right] was the vector with all zeros?
+
+ -
+
+The equation would have no solutions.
+
+
+ -
+
+The equation must have a unique solution.
+
+
+ -
+
+The equation must have infinitely-many solutions.
+
+
+
+
+
+ C.
-Note that (C) technically represents the equation
-x_1\vec{v}_1+x_2\vec{v}_2+x_3\vec{v}_3 =\vec w
-which isn't what was asked about.
+There cannot be contradictions, so its solutions are not unique.
@@ -324,20 +422,18 @@ which isn't what was asked about.
- For any vector space,
- the set \{\vec v_1,\dots\vec v_n\} is linearly dependent if and only
- if the vector equation x_1\vec v_1+ x_2 \vec v_2+\dots+x_n\vec v_n=\vec{0} is consistent with
- infinitely many solutions.
+The set \{\vec v_1,\dots,\vec v_n\} is linearly dependent
+exactly when the vector equation
+ x_1 \vec{v}_1 + \cdots + x_n\vec{v}_n = \vec{w}
+has infinitely-many solutions for some vector \vec{w}\in\IR^m
+(in particular, \vec w=\vec 0).
- Likewise, the set of vectors
- \{\vec v_1,\dots\vec v_n\} is linearly independent
- if and only the vector equation x_1\vec v_1+ x_2 \vec v_2 + \cdots + x_n\vec v_n = \vec{0}
- has exactly one solution: \left[\begin{array}{c}
- x_1 \\ \vdots \\ x_n
- \end{array}\right]=\left[\begin{array}{c}
- 0 \\ \vdots \\ 0
- \end{array}\right].
+On the other hand,
+the set \{\vec v_1,\dots,\vec v_n\} is linearly independent
+exactly when the vector equation
+ x_1 \vec{v}_1 + \cdots + x_n\vec{v}_n = \vec{w}
+has at most one solution for every vector \vec{w}\in\IR^m.
From d9689fec74d199539746501085fbb531f20862ac Mon Sep 17 00:00:00 2001
From: Steven Clontz
Date: Wed, 25 Feb 2026 19:12:55 +0000
Subject: [PATCH 2/2] add zero vector observation
---
source/linear-algebra/source/02-EV/04.ptx | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/source/linear-algebra/source/02-EV/04.ptx b/source/linear-algebra/source/02-EV/04.ptx
index 0850aeb2f..bbf58ddbf 100644
--- a/source/linear-algebra/source/02-EV/04.ptx
+++ b/source/linear-algebra/source/02-EV/04.ptx
@@ -433,7 +433,8 @@ On the other hand,
the set \{\vec v_1,\dots,\vec v_n\} is linearly independent
exactly when the vector equation
x_1 \vec{v}_1 + \cdots + x_n\vec{v}_n = \vec{w}
-has at most one solution for every vector \vec{w}\in\IR^m.
+has at most one solution for every vector \vec{w}\in\IR^m
+(and exactly one for \vec w=\vec 0).