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Exercises 20.6 Exercises

Determining membership in column space.

In each of the following, determine whether vector \(\uvec{v} \) is in the column space of matrix \(A \text{.}\) In those cases where it is, express \(\uvec{v} \) as a linear combination of the columns of \(A \text{.}\)

1.

\(A = \begin{abmatrix}{rrr} -1 \amp 7 \amp 3 \\ -1 \amp 6 \amp 3 \\ 2 \amp -8 \amp -5 \end{abmatrix} \text{;}\) \(\uvec{v} = \begin{abmatrix}{r} 4 \\ 3 \\ -4 \end{abmatrix} \)
Solution.
Vector \(\uvec{v} \) is in the column space of \(A \) precisely when the system \(A \uvec{x} = \uvec{v} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} -1 \amp 7 \amp 3 \amp 4 \\ -1 \amp 6 \amp 3 \amp 3 \\ 2 \amp -8 \amp -5 \amp -4 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 0 \amp -3 \\ 0 \amp 1 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp -2 \end{abmatrix} \end{equation*}
Since the system is consistent, \(\uvec{v} \) is in the column space of \(A \text{,}\) with
\begin{equation*} \uvec{v} = (-3) \begin{abmatrix}{r} -1 \\ -1 \\ 2 \end{abmatrix} + 1 \begin{abmatrix}{r} 7 \\ 6 \\ -8 \end{abmatrix} + (-2) \begin{abmatrix}{r} 3 \\ 3 \\ -5 \end{abmatrix}\text{.} \end{equation*}

2.

\(A = \begin{abmatrix}{rrr} 1 \amp -1 \amp 3 \\ 3 \amp -2 \amp 6 \\ 2 \amp -2 \amp 7 \\ -1 \amp 0 \amp -3 \end{abmatrix} \text{;}\) \(\uvec{v} = \begin{abmatrix}{r} 3 \\ 1 \\ 8 \\ 0 \end{abmatrix} \)
Solution.
Vector \(\uvec{v} \) is in the column space of \(A \) precisely when the system \(A \uvec{x} = \uvec{v} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} 1 \amp -1 \amp 3 \amp 3 \\ 3 \amp -2 \amp 6 \amp 1 \\ 2 \amp -2 \amp 7 \amp 8 \\ -1 \amp 0 \amp -3 \amp 0 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \\ \end{abmatrix} \end{equation*}
Since the system is inconsistent, \(\uvec{v} \) is not in the column space of \(A \text{.}\)

3.

\(A = \begin{abmatrix}{rrr} 1 \amp 1 \amp 6 \\ 0 \amp -1 \amp -1 \\ -1 \amp 1 \amp -4 \\ 1 \amp 3 \amp 8 \end{abmatrix} \text{;}\) \(\uvec{v} = \begin{abmatrix}{r} 1 \\ -4 \\ 7 \\ 9 \end{abmatrix} \)
Solution.
Vector \(\uvec{v} \) is in the column space of \(A \) precisely when the system \(A \uvec{x} = \uvec{v} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} 1 \amp 1 \amp 6 \amp 1 \\ 0 \amp -1 \amp -1 \amp -4 \\ -1 \amp 1 \amp -4 \amp 7 \\ 1 \amp 3 \amp 8 \amp 9 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 5 \amp -3 \\ 0 \amp 1 \amp 1 \amp 4 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
Since the system is consistent, \(\uvec{v} \) is in the column space of \(A \text{,}\) with
\begin{equation*} \uvec{v} = (-3) \begin{abmatrix}{r} 1 \\ 0 \\ -1 \\ 1 \end{abmatrix} + 4 \begin{abmatrix}{r} 1 \\ -1 \\ 1 \\ 3 \end{abmatrix} + 0 \begin{abmatrix}{r} 6 \\ -1 \\ -4 \\ 8 \end{abmatrix}\text{.} \end{equation*}

Determining membership in a span.

In each of the following, use column space to determine whether vector \(\uvec{v} \) is in \(\Span S \text{.}\) In those cases where it is, express \(\uvec{v} \) as a linear combination of the spanning set vectors.

4.

\(S = \{ (1, 1, 0, 0), (5, -4, 3, -5), (6, -6, 7, -7) \} \text{;}\) \(\uvec{v} = (1, -3, 8, -3) \)
Solution.
Create a matrix \(A \) whose columns are the vectors in \(S \text{:}\)
\begin{equation*} A = \begin{abmatrix}{rrr} 1 \amp 5 \amp 6 \\ 1 \amp -4 \amp -6 \\ 0 \amp 3 \amp 7 \\ 0 \amp -5 \amp -7 \end{abmatrix}\text{.} \end{equation*}
Then our question becomes whether \(\uvec{v} \) is in the column space of \(A \text{,}\) which happens precisely when the system \(A \uvec{x} = \uvec{v} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} 1 \amp 5 \amp 6 \amp 1 \\ 1 \amp -4 \amp -6 \amp -3 \\ 0 \amp 3 \amp 7 \amp 8 \\ 0 \amp -5 \amp -7 \amp -3 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \end{abmatrix} \end{equation*}
Since the system is inconsistent, \(\uvec{v} \) is not in \(\Span S \text{.}\)

5.

\(S = \{ (3, 2, 1, 0, 1), (4, 3, 1, 0, 3), (1, 1, -1, 0, 1) \} \text{;}\) \(\uvec{v} = (3,2,5,0,5) \)
Solution.
Create a matrix \(A \) whose columns are the vectors in \(S \text{:}\)
\begin{equation*} A = \begin{abmatrix}{rrr} 3 \amp 4 \amp 1 \\ 2 \amp 3 \amp 1 \\ 1 \amp 1 \amp -1 \\ 0 \amp 0 \amp 0 \\ 1 \amp 3 \amp 1 \end{abmatrix}\text{.} \end{equation*}
Then our question becomes whether \(\uvec{v} \) is in the column space of \(A \text{,}\) which happens precisely when the system \(A \uvec{x} = \uvec{v} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} 3 \amp 4 \amp 1 \amp 3 \\ 2 \amp 3 \amp 1 \amp 2 \\ 1 \amp 1 \amp -1 \amp 5 \\ 0 \amp 0 \amp 0 \amp 0 \\ 1 \amp 3 \amp 1 \amp 5 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 0 \amp -3 \\ 0 \amp 1 \amp 0 \amp 4 \\ 0 \amp 0 \amp 1 \amp -4 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
Since the system is consistent, \(\uvec{v} \) is in \(\Span S \text{,}\) with
\begin{equation*} \uvec{v} = (-3) \begin{bmatrix} 3 \\ 2 \\ 1 \\ 0 \\ 1 \end{bmatrix} + 4 \begin{abmatrix}{r} 4 \\ 3 \\ 1 \\ 0 \\ 3 \end{abmatrix} + (-4) \begin{abmatrix}{r} 1 \\ 1 \\ -1 \\ 0 \\ 1 \end{abmatrix}\text{.} \end{equation*}

6.

\(S = \left\{ \begin{bmatrix} 1 \amp 0 \\ 2 \amp 0 \end{bmatrix} , \begin{abmatrix}{rr} 2 \amp 1 \\ 3 \amp -1 \end{abmatrix}, \begin{bmatrix} 2 \amp 1 \\ 4 \amp 1 \end{bmatrix} \right\} \text{;}\) \(\uvec{v} = \begin{bmatrix} 3 \amp 2 \\ 8 \amp 6 \end{bmatrix} \)
Solution.
Create a matrix \(A \) whose columns are the coordinate vectors of the vectors in \(S \text{,}\) relative to the standard basis for \(\matrixring_{2 \times 2}(\R) \text{:}\)
\begin{equation*} A = \begin{abmatrix}{rrr} 1 \amp 2 \amp 2 \\ 0 \amp 1 \amp 1 \\ 2 \amp 3 \amp 4 \\ 0 \amp -1 \amp 1 \end{abmatrix}\text{.} \end{equation*}
Then our question becomes whether the coordinate vector for \(\uvec{v} \) is in the column space of \(A \text{,}\) which happens precisely when the system \(A \uvec{x} = \rmatrixOf{\uvec{v}}{S} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrr|r} 1 \amp 2 \amp 2 \amp 3 \\ 0 \amp 1 \amp 1 \amp 2 \\ 2 \amp 3 \amp 4 \amp 8 \\ 0 \amp -1 \amp 1 \amp 6 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|r} 1 \amp 0 \amp 0 \amp -1 \\ 0 \amp 1 \amp 0 \amp -2 \\ 0 \amp 0 \amp 1 \amp 4 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
Since the system is consistent, \(\uvec{v} \) is in \(\Span S \text{,}\) with
\begin{equation*} \uvec{v} = (-1) \begin{bmatrix} 1 \amp 0 \\ 2 \amp 0 \end{bmatrix} + (-2) \begin{abmatrix}{rr} 2 \amp 1 \\ 3 \amp -1 \end{abmatrix} + 4 \begin{bmatrix} 2 \amp 1 \\ 4 \amp 1 \end{bmatrix}\text{.} \end{equation*}

7.

\(S = \left\{ \begin{abmatrix}{rr} 2 \amp 0 \\ -1 \amp 0 \\ 1 \amp 1 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 1 \\ 0 \amp -1 \\ 0 \amp -1 \end{abmatrix}, \begin{abmatrix}{rr} -1 \amp 1 \\ 1 \amp -1 \\ -1 \amp 0 \end{abmatrix}, \begin{abmatrix}{rr} 2 \amp 4 \\ 1 \amp -3 \\ 0 \amp 1 \end{abmatrix} \right\}\)
\(\uvec{v} = \begin{abmatrix}{rr} 6 \amp 6 \\ 0 \amp -5 \\ 2 \amp 2 \end{abmatrix} \)
Solution.
Create a matrix \(A \) whose columns are the coordinate vectors of the vectors in \(S \text{,}\) relative to the standard basis for \(\matrixring_{3 \times 2}(\R) \text{:}\)
\begin{equation*} A = \begin{abmatrix}{rrrr} 2 \amp 0 \amp -1 \amp 2 \\ 0 \amp 1 \amp 1 \amp 4 \\ -1 \amp 0 \amp 1 \amp 1 \\ 0 \amp -1 \amp -1 \amp -3 \\ 1 \amp 0 \amp -1 \amp 0 \\ 1 \amp -1 \amp 0 \amp 1 \end{abmatrix}\text{.} \end{equation*}
Then our question becomes whether the coordinate vector for \(\uvec{v} \) is in the column space of \(A \text{,}\) which happens precisely when the system \(A \uvec{x} = \rmatrixOf{\uvec{v}}{S} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrrr|r} 2 \amp 0 \amp -1 \amp 2 \amp 6 \\ 0 \amp 1 \amp 1 \amp 4 \amp 6 \\ -1 \amp 0 \amp 1 \amp 1 \amp 0 \\ 0 \amp -1 \amp -1 \amp -3 \amp -5 \\ 1 \amp 0 \amp -1 \amp 0 \amp 2 \\ 1 \amp -1 \amp 0 \amp 1 \amp 2 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrr|r} 1 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
Since the system is inconsistent, \(\uvec{v} \) is not in \(\Span S \text{.}\)

8.

\begin{equation*} \begin{split} S = \{ \amp x^6 + x^5, x^6 + x^5 + x^2 - x + 1, x^6 - x^5 - x^4 + 3 x^3 + 3, \\ \amp 2 x^6 + 2 x^5 - x^3 + x^2 + 1, x^6 - 2 x^5 + 2 x^3 - 3 x^2 + x + 1 \} \end{split} \end{equation*}
\(\uvec{v} = 17 x^6 + 8 x^5 + 2 x^2 - 2 x + 14 \)
Solution.
The polynomials involved are all degree \(6 \text{,}\) so assume we are working in \(\poly_6(\R) \text{.}\) Create a matrix \(A \) whose columns are the coordinate vectors of the vectors in \(S \text{,}\) relative to the β€œreverse” standard basis for \(\poly_6(\R) \text{:}\)
\begin{equation*} A = \begin{abmatrix}{rrrrr} 1 \amp 1 \amp 1 \amp 2 \amp 1 \\ 1 \amp 1 \amp -1 \amp 2 \amp -2 \\ 0 \amp 0 \amp -1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 3 \amp -1 \amp 2 \\ 0 \amp 1 \amp 0 \amp 1 \amp -3 \\ 0 \amp -1 \amp 0 \amp 0 \amp 1 \\ 0 \amp 1 \amp 3 \amp 1 \amp 1 \end{abmatrix}\text{.} \end{equation*}
Then our question becomes whether the coordinate vector for \(\uvec{v} \) is in the column space of \(A \text{,}\) which happens precisely when the system \(A \uvec{x} = \rmatrixOf{\uvec{v}}{S} \) is consistent.
\begin{equation*} \begin{abmatrix}{rrrrr|r} 1 \amp 1 \amp 1 \amp 2 \amp 1 \amp 17 \\ 1 \amp 1 \amp -1 \amp 2 \amp -2 \amp 8 \\ 0 \amp 0 \amp -1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 3 \amp -1 \amp 2 \amp 0 \\ 0 \amp 1 \amp 0 \amp 1 \amp -3 \amp 2 \\ 0 \amp -1 \amp 0 \amp 0 \amp 1 \amp -2 \\ 0 \amp 1 \amp 3 \amp 1 \amp 1 \amp 14 \end{abmatrix} \;\; \rowredarrow \;\; \begin{abmatrix}{rrrrr|r} 1 \amp 0 \amp 0 \amp 0 \amp 0 \amp -3 \\ 0 \amp 1 \amp 0 \amp 0 \amp 0 \amp 5 \\ 0 \amp 0 \amp 1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \amp 0 \amp 6 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 3 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
Since the system is consistent, \(\uvec{v} \) is in \(\Span S \text{,}\) with
\begin{equation*} \begin{split} \uvec{v} = (-3) (x^6 + x^5) + 5 (x^6 + x^5 + x^2 - x + 1) + 0 (x^6 - x^5 - x^4 + 3 x^3 + 3) \\ + 6 (2 x^6 + 2 x^5 - x^3 + x^2 + 1) + 3 (x^6 - 2 x^5 + 2 x^3 - 3 x^2 + x + 1) \text{.} \end{split} \end{equation*}

Computing the three spaces.

In each of the following:
  1. State the value of \(k \) so that the column space of \(A \) is a subspace of \(\R^k \text{.}\)
  2. Form a basis for the column space of \(A \) from the columns of \(A \text{.}\)
  3. Do the columns of \(A \) span \(\R^k \text{,}\) where \(k \) is the value from partΒ a?
  4. Express each of the other columns of \(A \) as a linear combination of your basis vectors from partΒ b.
  5. State the value of \(k \) so that the row space of \(A \) is a subspace of \(\R^k \text{.}\)
  6. Determine a basis for the row space of \(A \text{.}\)
  7. Do the rows of \(A \) span \(\R^k \text{,}\) where \(k \) is the value from partΒ e?
  8. State the value of \(k \) so that the null space of \(A \) is a subspace of \(\R^k \text{.}\)
  9. Determine a basis for the null space of \(A \text{.}\)
  10. State the rank and nullity of \(A \text{,}\) and confirm the Rank-Nullity Theorem in this case.

9.

\(A = \begin{abmatrix}{rrr} 1 \amp 0 \amp 2 \\ -2 \amp 1 \amp -4 \\ 1 \amp 3 \amp 3 \end{abmatrix}\)
Answer.
\(\RREF(A) = I \)
  1. \(3 \) entries in each column \(\implies \) column space is a subspace of \(\R^3 \)
  2. Use all three columns of \(A \text{.}\)
  3. Yes.
  4. In this case, there are no β€œother” columns.
  5. \(3 \) entries in each row \(\implies \) row space is a subspace of \(\R^3 \)
  6. Use all three rows of \(\RREF(A) \) (the standard basis of \(\R^3 \)).
  7. Yes.
  8. System \(A \uvec{x} = \zerovec \) requires \(3 \) variable entries in \(\uvec{x} \) \(\implies \) null space is a subspace of \(\R^3 \text{.}\)
  9. Null space is the trivial space \(\{ \zerovec \} \text{,}\) with basis the empty set \(\{ \} \text{.}\)
  10. Rank is \(3 \) and nullity is \(0 \text{.}\) Sum of these is \(3 \text{,}\) which agrees with the number of columns of \(A \text{,}\) confirming the Rank-Nullity Theorem.

10.

\(A = \begin{abmatrix}{rrr} 0 \amp 1 \amp 4 \\ -1 \amp 1 \amp 1 \\ -1 \amp -1 \amp -7 \end{abmatrix}\)
Answer.
\(\RREF(A) = \begin{bmatrix} 1 \amp 0 \amp 3 \\ 0 \amp 1 \amp 4 \\ 0 \amp 0 \amp 0 \end{bmatrix}\)
  1. \(3 \) entries in each column \(\implies \) column space is a subspace of \(\R^3 \text{.}\)
  2. Use first two columns of \(A \text{;}\) column space is
    \begin{equation*} \Span \left\{ \begin{abmatrix}{r} 0 \\ -1 \\ -1 \end{abmatrix}, \begin{abmatrix}{r} 1 \\ 1 \\ -1 \end{abmatrix} \right\}\text{.} \end{equation*}
  3. No.
  4. Third column: \(\begin{abmatrix}{r} 4 \\ 1 \\ -7 \end{abmatrix} = 3 \begin{abmatrix}{r} 0 \\ -1 \\ -1 \end{abmatrix} + 4 \begin{abmatrix}{r} 1 \\ 1 \\ -1 \end{abmatrix} \text{.}\)
  5. \(3 \) entries in each row \(\implies \) row space is a subspace of \(\R^3 \)
  6. Use nonzero rows of \(\RREF(A) \text{;}\) row space is
    \begin{equation*} \Span \left\{ \begin{bmatrix} 1 \amp 0 \amp 3 \end{bmatrix}, \begin{bmatrix} 0 \amp 1 \amp 4 \end{bmatrix} \right\}\text{.} \end{equation*}
  7. No.
  8. System \(A \uvec{x} = \zerovec \) requires \(3 \) variable entries in \(\uvec{x} \) \(\implies \) null space is a subspace of \(\R^3 \text{.}\)
  9. Null space is \(\Span \left\{ \begin{abmatrix}{r} -3 \\ -4 \\ 1 \end{abmatrix} \right\} \text{.}\)
  10. Rank is \(2 \) and nullity is \(1 \text{.}\) Sum of these is \(3 \text{,}\) which agrees with the number of columns of \(A \text{,}\) confirming the Rank-Nullity Theorem.

11.

\(A = \begin{abmatrix}{rrr} 1 \amp - 7 \amp -2 \\ -3 \amp 21 \amp 1 \\ 0 \amp 0 \amp 1 \\ 2 \amp -14 \amp 2 \end{abmatrix}\)
Answer.
\(\RREF(A) = \begin{abmatrix}{rrr} 1 \amp -7 \amp 0 \\ 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \end{abmatrix}\)
  1. \(4 \) entries in each column \(\implies \) column space is a subspace of \(\R^4 \text{.}\)
  2. Use first and third columns; column space is
    \begin{equation*} \Span \left\{ \begin{abmatrix}{r} 1 \\ -3 \\ 0 \\ 2 \end{abmatrix}, \begin{abmatrix}{r} -2 \\ 1 \\ 1 \\ 2 \end{abmatrix} \right\}\text{.} \end{equation*}
  3. No.
  4. Second column: \(\begin{abmatrix}{r} -7 \\ 21 \\ 0 \\ -14 \end{abmatrix} = 7 \begin{abmatrix}{r} 1 \\ -3 \\ 0 \\ 2 \end{abmatrix} + 0 \begin{abmatrix}{r} -2 \\ 1 \\ 1 \\ 2 \end{abmatrix} \text{.}\)
  5. \(3 \) entries in each row \(\implies \) row space is a subspace of \(\R^3 \text{.}\)
  6. Use nonzero rows of \(\RREF(A) \text{;}\) row space is
    \begin{equation*} \Span \left\{ \begin{bmatrix} 1 \amp -7 \amp 0 \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \amp 1 \end{bmatrix} \right\}\text{.} \end{equation*}
  7. No.
  8. System \(A \uvec{x} = \zerovec \) requires \(3 \) variable entries in \(\uvec{x} \) \(\implies \) null space is a subspace of \(\R^3 \text{.}\)
  9. Null space is \(\Span \left\{ \begin{abmatrix}{r} 7 \\ 1 \\ 0 \end{abmatrix} \right\} \text{.}\)
  10. Rank is \(2 \) and nullity is \(1 \text{.}\) Sum of these is \(3 \text{,}\) which agrees with the number of columns of \(A \text{,}\) confirming the Rank-Nullity Theorem.

12.

\(A = \begin{abmatrix}{rrrrr} -2 \amp -2 \amp 8 \amp 1 \amp 11 \\ 1 \amp 1 \amp - 4 \amp -1 \amp - 5 \\ 3 \amp 2 \amp -13 \amp -1 \amp -10 \\ -1 \amp 1 \amp 6 \amp 0 \amp - 8 \end{abmatrix}\)
Answer.
\(\RREF(A) = \begin{abmatrix}{rrrrr} 1 \amp 0 \amp -5 \amp 0 \amp 1 \\ 0 \amp 1 \amp 1 \amp 0 \amp -7 \\ 0 \amp 0 \amp 0 \amp 1 \amp -1 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix}\)
  1. \(4 \) entries in each column \(\implies \) column space is a subspace of \(\R^4 \text{.}\)
  2. Use first, second, and fourth columns; column space is
    \begin{equation*} \Span \left\{ \begin{abmatrix}{r} -2 \\ 1 \\ 3 \\ -1 \end{abmatrix}, \begin{abmatrix}{r} -2 \\ 1 \\ 2 \\ 1 \end{abmatrix}, \begin{abmatrix}{r} 1 \\ -1 \\ -1 \\ 0 \end{abmatrix} \right\}\text{.} \end{equation*}
  3. No.
  4. Third column:
    \begin{equation*} \begin{abmatrix}{r} 8 \\ -4 \\ -13 \\ 6 \end{abmatrix} = -5 \begin{abmatrix}{r} -2 \\ 1 \\ 3 \\ -1 \end{abmatrix} + 1 \begin{abmatrix}{r} -2 \\ 1 \\ 2 \\ 1 \end{abmatrix} + 0 \begin{abmatrix}{r} 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
    Fifth column:
    \begin{equation*} \begin{abmatrix}{r} 11 \\ -5 \\ -10 \\ -8 \end{abmatrix} = 1 \begin{abmatrix}{r} -2 \\ 1 \\ 3 \\ -1 \end{abmatrix} + (-7) \begin{abmatrix}{r} -2 \\ 1 \\ 2 \\ 1 \end{abmatrix} + (-1) \begin{abmatrix}{r} 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
  5. \(5 \) entries in each row \(\implies \) so the row space is a subspace of \(\R^5 \text{.}\)
  6. Use nonzero rows of \(\RREF(A) \text{;}\) row space is
    \begin{equation*} \Span \{ \begin{bmatrix} 1 \amp 0 \amp -5 \amp 0 \amp 1 \end{bmatrix}, \begin{bmatrix} 0 \amp 1 \amp 1 \amp 0 \amp -7 \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \amp 0 \amp 1 \amp -1 \end{bmatrix} \}\text{.} \end{equation*}
  7. No.
  8. System \(A \uvec{x} = \zerovec \) requires \(5 \) variable entries in \(\uvec{x} \) \(\implies \) null space is a subspace of \(\R^5 \text{.}\)
  9. Null space is \(\Span \left\{ \begin{abmatrix}{r} 5 \\ -1 \\ 1 \\ 0 \\ 0 \end{abmatrix}, \begin{abmatrix}{r} -1 \\ 7 \\ 0 \\ 1 \\ 1 \end{abmatrix} \right\} \text{.}\)
  10. Rank is \(3 \) and nullity is \(2 \text{.}\) Sum of these is \(5 \text{,}\) which agrees with the number of columns of \(A \text{,}\) confirming the Rank-Nullity Theorem.

13.

\(A = \begin{abmatrix}{rrrrrrr} -1 \amp -2 \amp 14 \amp -20 \amp 0 \amp 4 \amp 18 \\ -1 \amp 2 \amp -14 \amp 16 \amp 1 \amp -9 \amp -12 \\ 2 \amp 1 \amp - 7 \amp 13 \amp -1 \amp 1 \amp -14 \\ 0 \amp -3 \amp 21 \amp -27 \amp -1 \amp 9 \amp 22 \\ 1 \amp 1 \amp - 7 \amp 11 \amp 0 \amp 0 \amp -10 \end{abmatrix}\)
Answer.
\(\RREF(A) = \begin{abmatrix}{rrrrrrr} 1 \amp 0 \amp 0 \amp 2 \amp 0 \amp 4 \amp -2 \\ 0 \amp 1 \amp -7 \amp 9 \amp 0 \amp -4 \amp -8 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 3 \amp 2 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix}\)
  1. \(5 \) entries in each column \(\implies \) so the column space is a subspace of \(\R^5 \text{.}\)
  2. Use first, second, and fifth columns; column space is
    \begin{equation*} \Span \left\{ \begin{abmatrix}{r} -1 \\ -1 \\ 2 \\ 0 \\ 1 \end{abmatrix}, \begin{abmatrix}{r} -2 \\ 2 \\ 1 \\ -3 \\ 1 \end{abmatrix}, \begin{abmatrix}{r} 0 \\ 1 \\ -1 \\ -1 \\ 0 \end{abmatrix} \right\}\text{.} \end{equation*}
  3. No.
  4. Third column:
    \begin{equation*} \begin{abmatrix}{r} 14 \\ -14 \\ -7 \\ 21 \\ -7 \end{abmatrix} = 0 \begin{abmatrix}{r} -1 \\ -1 \\ 2 \\ 0 \\ 1 \end{abmatrix} + (-7) \begin{abmatrix}{r} -2 \\ 2 \\ 1 \\ -3 \\ 1 \end{abmatrix} + 0 \begin{abmatrix}{r} 0 \\ 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
    Fourth column:
    \begin{equation*} \begin{abmatrix}{r} -20 \\ 16 \\ 13 \\ -27 \\ 11 \end{abmatrix} = 2 \begin{abmatrix}{r} -1 \\ -1 \\ 2 \\ 0 \\ 1 \end{abmatrix} + 9 \begin{abmatrix}{r} -2 \\ 2 \\ 1 \\ -3 \\ 1 \end{abmatrix} + 0 \begin{abmatrix}{r} 0 \\ 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
    Sixth column:
    \begin{equation*} \begin{abmatrix}{r} 4 \\ -9 \\ 1 \\ 9 \\ 0 \end{abmatrix} = 4 \begin{abmatrix}{r} -1 \\ -1 \\ 2 \\ 0 \\ 1 \end{abmatrix} + (-4) \begin{abmatrix}{r} -2 \\ 2 \\ 1 \\ -3 \\ 1 \end{abmatrix} + 3 \begin{abmatrix}{r} 0 \\ 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
    Seventh column:
    \begin{equation*} \begin{abmatrix}{r} 18 \\ -12 \\ -14 \\ 22 \\ -10 \end{abmatrix} = (-2) \begin{abmatrix}{r} -1 \\ -1 \\ 2 \\ 0 \\ 1 \end{abmatrix} + (-8) \begin{abmatrix}{r} -2 \\ 2 \\ 1 \\ -3 \\ 1 \end{abmatrix} + 2 \begin{abmatrix}{r} 0 \\ 1 \\ -1 \\ -1 \\ 0 \end{abmatrix}\text{.} \end{equation*}
  5. \(7 \) entries in each row \(\implies \) so the row space is a subspace of \(\R^7 \text{.}\)
  6. Use nonzero rows of \(\RREF(A) \text{;}\) row space is
    \begin{equation*} \begin{split} \Span \{ \begin{bmatrix} 1 \amp 0 \amp 0 \amp 2 \amp 0 \amp 4 \amp -2 \end{bmatrix}, \begin{bmatrix} 0 \amp 1 \amp -7 \amp 9 \amp 0 \amp -4 \amp -8 \end{bmatrix}, \\ \begin{bmatrix} 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 3 \amp 2 \end{bmatrix} \} \text{.} \end{split} \end{equation*}
  7. No.
  8. As the coefficient matrix of a homogeneous system, there are \(7 \) variable coefficients in each row, so each equation in the homogeneous system would involve \(7 \) variables. Therefore, the null space is a subspace of \(\R^7 \text{.}\)
  9. Null space is \(\Span \left\{ \begin{abmatrix}{r} 0 \\ 7 \\ 1 \\ 0 \\ 0 \\ 0 \\ 0 \end{abmatrix}, \begin{abmatrix}{r} -2 \\ -9 \\ 0 \\ 1 \\ 0 \\ 0 \\ 0 \end{abmatrix}, \begin{abmatrix}{r} -4 \\ 4 \\ 0 \\ 0 \\ -3 \\ 1 \\ 0 \end{abmatrix}, \begin{abmatrix}{r} 2 \\ 8 \\ 0 \\ 0 \\ -2 \\ 0 \\ 1 \end{abmatrix} \right\} \text{.}\)
  10. Rank is \(3 \) and nullity is \(4 \text{.}\) Sum of these is \(7 \text{,}\) which agrees with the number of columns of \(A \text{,}\) confirming the Rank-Nullity Theorem.

Size versus rank and nullity.

In each of the following, determine the size of a matrix that has rank \(r \text{,}\) nullity \(z \text{,}\) and whose column space is a subspace of \(\R^k \text{,}\) or state why such a matrix is not possible.

17.

\(r = 6 \text{,}\) \(z = 2 \text{,}\) \(k = 5 \)
Answer.
Not possible: need at least \(6 \) rows to fit rank \(6 \text{.}\)

Reducing a spanning set.

In each of the following, a spanning set for a subspace \(W \) of a vector space \(V \) is provided. Use ProcedureΒ 20.3.2 to reduce the spanning set to a basis for \(W \text{.}\)

18.

\(V = \R^4 \)
\(W = \Span \{ (1,0,1,1), (-3,3,7,1), (-1,3,9,3), (-5,3,5,-1) \} \)
Solution.
Use the vectors as columns in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 1 \amp -3 \amp -1 \amp -5 \\ 0 \amp 3 \amp 3 \amp 3 \\ 1 \amp 7 \amp 9 \amp 5 \\ 1 \amp 1 \amp 3 \amp -1 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 2 \amp -2 \\ 0 \amp 1 \amp 1 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
From the position of the leading ones in the reduced matrix we see that
\begin{equation*} W = \Span \{ (1,0,1,1), (-3,3,7,1) \} \text{.} \end{equation*}

19.

\(V = \R^5 \)
\begin{equation*} \begin{split} W = \Span \{ (3,-1,1,-1,-2), (4,-1,2,-2,-2), (17,-4,9,-9,-8), \\ (1,-1,1,1,-1) \} \end{split} \end{equation*}
Solution.
Use the vectors as columns in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 3 \amp 4 \amp 17 \amp 1 \\ -1 \amp -1 \amp -4 \amp -1 \\ 1 \amp 2 \amp 9 \amp 1 \\ -1 \amp -2 \amp -9 \amp 1 \\ -2 \amp -2 \amp -8 \amp -1 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrr} 1 \amp 0 \amp -1 \amp 0 \\ 0 \amp 1 \amp 5 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
From the position of the leading ones in the reduced matrix we see that
\begin{equation*} W = \Span \{ (3,-1,1,-1,-2), (4,-1,2,-2,-2), (1,-1,1,1,-1) \} \text{.} \end{equation*}

20.

\(V = \matrixring_{2 \times 2}(\R) \)
\begin{equation*} \begin{split} W = \Span \left\{ \begin{abmatrix}{rr} 1 \amp -1 \\ 5 \amp 2 \end{abmatrix}, \begin{abmatrix}{rr} -2 \amp 3 \\ 1 \amp 0 \end{abmatrix}, \begin{abmatrix}{rr} 4 \amp -5 \\ 9 \amp 4 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 4 \\ 2 \amp -3 \end{abmatrix}, \right. \\ \left. \begin{abmatrix}{rr} -7 \amp 18 \\ 2 \amp -8 \end{abmatrix} \right\} \end{split} \end{equation*}
Solution.
Use the entries of the matrices (that is, the coordinates relative to the standard basis of \(V \)) as column vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrrr} 1 \amp -2 \amp 4 \amp 0 \amp -7 \\ -1 \amp 3 \amp -5 \amp 4 \amp 18 \\ 5 \amp 1 \amp 9 \amp 2 \amp 2 \\ 2 \amp 0 \amp 4 \amp -3 \amp -8 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 0 \amp 2 \amp 0 \amp -1 \\ 0 \amp 1 \amp -1 \amp 0 \amp 3 \\ 0 \amp 0 \amp 0 \amp 1 \amp 2 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
From the position of the leading ones in the reduced matrix we see that
\begin{equation*} W = \Span \left\{ \begin{abmatrix}{rr} 1 \amp -1 \\ 5 \amp 2 \end{abmatrix}, \begin{abmatrix}{rr} -2 \amp 3 \\ 1 \amp 0 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 4 \\ 2 \amp -3 \end{abmatrix} \right\}\text{.} \end{equation*}

21.

\(V = \poly_3(\R) \)
\(W = \Span \{ 1 - 2 x + 3 x^3, 2 - 4 x + 6 x^3, -1 + x + 2 x^2, - x + 2 x^2 + 3 x^3 \} \)
Solution.
Use the coefficients of the polynomials (that is, the coordinates relative to the standard basis of \(V \)) as column vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 1 \amp 2 \amp -1 \amp 0 \\ -2 \amp -4 \amp 1 \amp -1 \\ 0 \amp 0 \amp 2 \amp 2 \\ 3 \amp 6 \amp 0 \amp 3 \end{abmatrix} \qquad \rowredarrow \qquad \begin{bmatrix} 1 \amp 2 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{bmatrix} \end{equation*}
From the position of the leading ones in the reduced matrix we see that
\begin{equation*} W = \Span \{ 1 - 2 x + 3 x^3, -1 + x + 2 x^2 \} \text{.} \end{equation*}

22.

\(V = \poly_6(\R) \)
\begin{equation*} \begin{split} W = \Span \{ \amp 1 - x^2 - x^3 + 2 x^4 + x^5 - x^6, x + x^2 - x^6, \\ \amp -2 + 9 x + 11 x^2 + 2 x^3 - 4 x^4 - 2 x^5 - 7 x^6, \\ \amp 4 - 4 x - 8 x^2 - 4 x^3 + 8 x^4 + 4 x^5, x^2 + 2 x^3 - x^4 - x^6 \} \end{split} \end{equation*}
Solution.
Use the coefficients of the polynomials (that is, the coordinates relative to the standard basis of \(V \)) as column vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrrr} 1 \amp 0 \amp -2 \amp 4 \amp 0 \\ 0 \amp 1 \amp 9 \amp -4 \amp 0 \\ -1 \amp 1 \amp 11 \amp -8 \amp 1 \\ -1 \amp 0 \amp 2 \amp -4 \amp 2 \\ 2 \amp 0 \amp -4 \amp 8 \amp -1 \\ 1 \amp 0 \amp -2 \amp 4 \amp 0 \\ -1 \amp -1 \amp -7 \amp 0 \amp -1 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 0 \amp -2 \amp 4 \amp 0 \\ 0 \amp 1 \amp 9 \amp -4 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
From the position of the leading ones in the reduced matrix we see that
\begin{equation*} W = \Span \{ 1 - x^2 - x^3 + 2 x^4 + x^5 - x^6, x + x^2 - x^6, x^2 + 2 x^3 - x^4 - x^6 \}\text{.} \end{equation*}

Subspace Test via row reduction.

In each of the following, two sets \(S \) and \(S' \) of vectors from a vector space \(V \) have been provided. Combine column space with StatementΒ 1 of StatementΒ 16.5.6 to test whether \(\Span S \) is a subspace of \(\Span S' \text{.}\)

23.

\(V = \R^4 \)
\(S = \{ (1, -9, 7, 1), (1, 0, -2, 2) \} \)
\(S' = \{ (1, -5, -2, -4), (0, 1, -1, 0), (0, 0, 1, 1) \} \)
Solution.
Instead of testing whether each vector in \(S \) is in \(\Span S' \) one-by-one, we can test all simultaneously by augmenting the matrix of \(S' \) vectors (as columns) with all vectors in \(S \) (again as columns). Then reduce.
\begin{equation*} \begin{abmatrix}{rrr|rr} 1 \amp 0 \amp 0 \amp 1 \amp 1 \\ -5 \amp 1 \amp 0 \amp -9 \amp 0 \\ -2 \amp -1 \amp 1 \amp 7 \amp -2 \\ -4 \amp 0 \amp 1 \amp 1 \amp 2 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr|rr} 1 \amp 0 \amp 0 \amp 1 \amp 0 \\ 0 \amp 1 \amp 0 \amp -4 \amp 0 \\ 0 \amp 0 \amp 1 \amp 5 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \end{abmatrix} \end{equation*}
The reduced matrix demonstrates that the fourth column is dependent with the first three, but the fifth column is independent. So while the first vector in \(S \) is in \(\Span S' \text{,}\) the second vector in \(S \) is not. Therefore, \(\Span S \) is not a subspace of \(\Span S' \text{.}\)

24.

\(V = \R^5 \)
\(S = \{ (5, 5, 0, -2, -2,), (2, 2, 2, 0, 1) \} \)
\(S' = \{ (1, 1, 0, -1, -1), (-1, 1, 4, 1, 0), (1, 0, -1, -1, 0), (2, 0, -2, -3, -1) \} \)
Solution.
Instead of testing whether each vector in \(S \) is in \(\Span S' \) one-by-one, we can test all simultaneously by augmenting the matrix of \(S' \) vectors (as columns) with all vectors in \(S \) (again as columns). Then reduce.
\begin{equation*} \begin{abmatrix}{rrrr|rr} 1 \amp -1 \amp 1 \amp 2 \amp 5 \amp 2 \\ 1 \amp 1 \amp 0 \amp 0 \amp 5 \amp 2 \\ 0 \amp 4 \amp -1 \amp -2 \amp 0 \amp 2 \\ -1 \amp 1 \amp -1 \amp -3 \amp -2 \amp 0 \\ -1 \amp 0 \amp 0 \amp -1 \amp -2 \amp 1 \end{abmatrix} \; \rowredarrow \; \begin{abmatrix}{rrrr|rr} 1 \amp 0 \amp 0 \amp 0 \amp 5 \amp 1 \\ 0 \amp 1 \amp 0 \amp 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp 0 \amp 6 \amp 6 \\ 0 \amp 0 \amp 0 \amp 1 \amp -3 \amp -2 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
The reduced matrix demonstrates that both the fifth and sixth columns are dependent with the first four, so both vectors in \(S \) are in \(\Span S' \text{.}\) Therefore, \(\Span S \) is a subspace of \(\Span S' \text{.}\)

25.

\(V = \matrixring_{2 \times 2}(\R) \)
\(S = \left\{ \begin{abmatrix}{rr} 1 \amp 1 \\ -3 \amp 3 \end{abmatrix}, \begin{abmatrix}{rr} 1 \amp 7 \\ 6 \amp -9 \end{abmatrix}, \begin{abmatrix}{rr} 4 \amp 0 \\ -3 \amp 5 \end{abmatrix} \right\}\)
\(S' = \left\{ \begin{abmatrix}{rr} 1 \amp -1 \\ -2 \amp 3 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 0 \\ 1 \amp -1 \end{abmatrix}, \begin{abmatrix}{rr} 1 \amp 1 \\ 0 \amp 0 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp -2 \\ 2 \amp -1 \end{abmatrix} \right\}\)
Solution.
Instead of testing whether each vector in \(S \) is in \(\Span S' \) one-by-one, we can test all simultaneously by augmenting the matrix of \(S' \) vectors (using their coordinate vectors relative to the standard basis of \(V \) as columns) with all vectors in \(S \) (again using coordinate vectors as columns). Then reduce.
\begin{equation*} \begin{split} \amp \begin{abmatrix}{rrrr|rrr} 1 \amp 0 \amp 1 \amp 0 \amp 1 \amp 1 \amp 4 \\ -1 \amp 0 \amp 1 \amp -2 \amp 1 \amp 7 \amp 0 \\ -2 \amp 1 \amp 0 \amp 2 \amp -3 \amp 6 \amp -3 \\ 3 \amp -1 \amp 0 \amp -1 \amp 3 \amp -9 \amp 5 \end{abmatrix} \\ \amp \quad \rowredarrow \qquad \begin{abmatrix}{rrrr|rrr} 1 \amp 0 \amp 0 \amp 1 \amp 0 \amp -3 \amp 2 \\ 0 \amp 1 \amp 0 \amp 4 \amp -3 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp -1 \amp 1 \amp 4 \amp 2 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{split} \end{equation*}
The reduced matrix demonstrates that each of the fifth, sixth and seventh columns are dependent with the first four (in fact, with just the first three columns), so all vectors in \(S \) are in \(\Span S' \text{.}\) Therefore, \(\Span S \) is a subspace of \(\Span S' \text{.}\)

26.

\(V = \poly_5(\R) \)
\begin{equation*} \begin{split} S = \{ 3 x^5 - x^4 - 5 x^3 + 4 x^2 - 4 x - 7, 4 x^5 + 5 x^4 - x^3 - 2 x^2 + 1 x + 4, \\ 4 x^5 - 3 x^4 + x^3 + - 2 x + 6 \} \end{split} \end{equation*}
\begin{equation*} \begin{split} S' = \{ x^5 - x^3 - 1, x^5 - x^4 - 1, - x^4 + x^2 - x - 1, x^5 + x^4 - x^2 + x , \\ 2 x^5 + 3 x^3 - 2 x^2 + x + 5 \} \end{split} \end{equation*}
Solution.
Instead of testing whether each vector in \(S \) is in \(\Span S' \) one-by-one, we can test all simultaneously by augmenting the matrix of \(S' \) vectors (using their coordinate vectors relative to the β€œreverse” standard basis \(\{ x^5, x^4, x^3, x^2, x, 1 \} \) of \(V \) as columns) with all vectors in \(S \) (again using coordinate vectors as columns). Then reduce.
\begin{equation*} \begin{split} \amp \begin{abmatrix}{rrrrr|rrr} 1 \amp 1 \amp 0 \amp 1 \amp 2 \amp 3 \amp 4 \amp 4 \\ 0 \amp -1 \amp -1 \amp 1 \amp 0 \amp -1 \amp 5 \amp -3 \\ -1 \amp 0 \amp 0 \amp 0 \amp 3 \amp -5 \amp -1 \amp 1 \\ 0 \amp 0 \amp 1 \amp -1 \amp -2 \amp 4 \amp -2 \amp 0 \\ 0 \amp 0 \amp -1 \amp 1 \amp 1 \amp -4 \amp 1 \amp -2 \\ -1 \amp -1 \amp -1 \amp 0 \amp 5 \amp -7 \amp 4 \amp 6 \end{abmatrix} \\ \amp \quad \rowredarrow \qquad \begin{abmatrix}{rrrrr|rrr} 1 \amp 0 \amp 0 \amp 0 \amp 0 \amp 5 \amp 0 \amp 5 \\ 0 \amp 1 \amp 0 \amp 0 \amp 0 \amp -3 \amp 0 \amp -1 \\ 0 \amp 0 \amp 1 \amp 0 \amp 0 \amp 5 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \amp 0 \amp 1 \amp 0 \amp -4 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 0 \amp 0 \amp 2 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 0 \end{abmatrix} \end{split} \end{equation*}
The reduced matrix demonstrates that each of the sixth and eighth columns are dependent with the first five, but the seventh column is independent. So while the first and third vectors in \(S \) are in \(\Span S' \text{,}\) the second vector in \(S \) is not. Therefore, \(\Span S \) is not a subspace of \(\Span S' \text{.}\)

Simplifying a basis.

In each of the following, a basis for a subspace \(W \) of a vector space \(V \) is been provided. Use ProcedureΒ 20.3.6 to create a β€œsimplified” basis for \(W \text{.}\)

27.

\(V = \R^5 \)
\(W = \Span \{ (-2,3,2,-7,6), (-1,1,1,-4,4), (-2,5,3,-8,7) \} \)
Solution.
Use the vectors as rows in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrrr} -2 \amp 3 \amp 2 \amp -7 \amp 6 \\ -1 \amp 1 \amp 1 \amp -4 \amp 4 \\ -2 \amp 5 \amp 3 \amp -8 \amp 7 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 0 \amp 0 \amp 2 \amp -1 \\ 0 \amp 1 \amp 0 \amp 1 \amp -2 \\ 0 \amp 0 \amp 1 \amp -3 \amp 5 \end{abmatrix} \end{equation*}
Since the original and reduced matrices have the same row space,
\begin{equation*} W = \Span \{ (1,0,0,2,-1), (0,1,0,1,-2), (0,0,1,-3,5) \} \text{.} \end{equation*}

28.

\(V = \matrixring_{2 \times 3}(\R) \)
\begin{equation*} \begin{split} W = \Span \left\{ \begin{abmatrix}{rrr} -2 \amp 5 \amp -4 \\ 1 \amp -8 \amp -6 \end{abmatrix}, \begin{abmatrix}{rrr} 3 \amp -4 \amp 0 \\ 7 \amp 6 \amp -1 \end{abmatrix}, \begin{abmatrix}{rrr} -1 \amp 5 \amp -7 \\ 7 \amp -8 \amp -8 \end{abmatrix}, \right. \\ \left. \begin{abmatrix}{rrr} 1 \amp -1 \amp 0 \\ 4 \amp 3 \amp 4 \end{abmatrix} \right\} \end{split} \end{equation*}
Solution.
Use the entries of the matrices (that is, the coordinates relative to the standard basis of \(V \)) as row vectors in a matrix and reduce.
\begin{align*} \amp \begin{abmatrix}{rrrrr} -2 \amp 5 \amp -4 \amp 1 \amp -8 \amp -6 \\ 3 \amp -4 \amp 0 \amp 7 \amp 6 \amp -1 \\ -1 \amp 5 \amp -7 \amp 7 \amp -8 \amp -8 \\ 1 \amp -1 \amp 0 \amp 4 \amp 3 \amp 4 \end{abmatrix}\\ \amp \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 0 \amp 0 \amp 0 \amp -\frac{15}{2} \amp -\frac{71}{2} \\ 0 \amp 1 \amp 0 \amp 0 \amp -\frac{ 9}{2} \amp -\frac{97}{6} \\ 0 \amp 0 \amp 1 \amp 0 \amp \frac{ 1}{2} \amp \frac{ 1}{2} \\ 0 \amp 0 \amp 0 \amp 1 \amp \frac{ 3}{2} \amp \frac{35}{6} \end{abmatrix} \end{align*}
Since the original and reduced matrices have the same row space,
\begin{equation*} \begin{split} W = \Span \left\{ \begin{bmatrix} 1 \amp 0 \amp 0 \\ 0 \amp -\frac{15}{2} \amp -\frac{71}{2} \end{bmatrix}, \begin{bmatrix} 0 \amp 1 \amp 0 \\ 0 \amp -\frac{ 9}{2} \amp -\frac{97}{6} \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \amp 1 \\ 0 \amp \frac{ 1}{2} \amp \frac{ 1}{2} \end{bmatrix}, \right. \\ \left. \begin{bmatrix} 0 \amp 0 \amp 0 \\ 1 \amp \frac{ 3}{2} \amp \frac{35}{6} \end{bmatrix} \right\} \text{.} \end{split} \end{equation*}

29.

\(V = \poly_4(\R) \)
\begin{equation*} \begin{split} W = \Span \{ -2 + x - x^2 + 4 x^3 - 2 x^4, 2 + 2 x - x^2 - x^3 - 3 x^4, \\ 2 x - 2 x^2 + x^3 - 6 x^4, 3 - x^2 - 7 x^3 - 5 x^4 \} \end{split} \end{equation*}
Solution.
Use the coefficients of the polynomials in reverse order (that is, the coordinates relative to the β€œreversed” standard basis \(\{ x^4, x^3, x^2, x, 1 \} \) of \(V \)) as row vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrrr} -2 \amp 4 \amp -1 \amp 1 \amp -2 \\ -3 \amp -1 \amp -1 \amp 2 \amp 2 \\ -6 \amp 1 \amp -2 \amp 2 \amp 0 \\ -5 \amp -7 \amp -1 \amp 0 \amp 3 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 0 \amp 0 \amp 0 \amp -\frac{1}{4} \\ 0 \amp 1 \amp 0 \amp 0 \amp -\frac{1}{2} \\ 0 \amp 0 \amp 1 \amp 0 \amp \frac{7}{4} \\ 0 \amp 0 \amp 0 \amp 1 \amp \frac{5}{4} \end{abmatrix} \end{equation*}
Since the original and reduced matrices have the same row space,
\begin{equation*} W = \Span \left\{ x^4 - \tfrac{1}{4}, x^3 - \tfrac{1}{2}, x^2 + \tfrac{7}{4}, x + \tfrac{5}{4} \right\} \text{.} \end{equation*}
Note. The reason we chose to reverse the order of the coefficients is so that each basis polynomial is monic, and the basis polynomials all have different degrees.

Enlarging an independent set.

In each of the following, an independent set \(S \) of vectors from a vector space \(V \) is provided. Enlarge \(S \) to a basis for \(V \text{.}\)

30.

\(V = \R^5 \)
\(S = \{ (-2,-8,5,-1,34), (3,12,-8,0,-62), (1,4,-3,0,-23) \} \)
Solution.
Use the vectors as rows in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrrr} -2 \amp -8 \amp 5 \amp -1 \amp 34 \\ 3 \amp 12 \amp -8 \amp 0 \amp -62 \\ 1 \amp 4 \amp -3 \amp 0 \amp -23 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrrr} 1 \amp 4 \amp 0 \amp 0 \amp -2 \\ 0 \amp 0 \amp 1 \amp 0 \amp 7 \\ 0 \amp 0 \amp 0 \amp 1 \amp 5 \end{abmatrix} \end{equation*}
The reduced vectors exhibit independence in the first, third, and fourth components. So we can extend to a basis by β€œfilling in” the second and fifth standard basis vectors:
\begin{equation*} \begin{split} \R^5 = \Span \{ (-2,-8,5,-1,34), (3,12,-8,0,-62), (1,4,-3,0,-23), \\ (0,1,0,0,0), (0,0,0,0,1) \} \text{.} \end{split} \end{equation*}

31.

\(V = \R^7 \)
\begin{equation*} \begin{split} S = \{ (2,1,-3,4,1,1,-10), (1,5,3,-34,4,-3,23), (-2,-2,2,4,-2,1,5), \\ (3,6,0,-30,6,-7,8) \} \end{split} \end{equation*}
Solution.
Use the vectors as rows in a matrix and reduce.
\begin{align*} \amp \begin{abmatrix}{rrrrrrr} 2 \amp 1 \amp -3 \amp 4 \amp 1 \amp 1 \amp -10 \\ 1 \amp 5 \amp 3 \amp -34 \amp 4 \amp -3 \amp 23 \\ -2 \amp -2 \amp 2 \amp 4 \amp -2 \amp 1 \amp 5 \\ 3 \amp 6 \amp 0 \amp -30 \amp 6 \amp -7 \amp 8 \end{abmatrix}\\ \amp \rowredarrow \qquad \begin{abmatrix}{rrrrrrr} 1 \amp 0 \amp -2 \amp 6 \amp 0 \amp 0 \amp -9 \\ 0 \amp 1 \amp 1 \amp -8 \amp 0 \amp 0 \amp 7 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 1 \end{abmatrix} \end{align*}
The reduced vectors exhibit independence in the first, second, fifth, and sixth components. So we can extend to a basis by β€œfilling in” the third, fourth, and seventh standard basis vectors:
\begin{equation*} \begin{split} \R^5 = \Span \{ (2,1,-3,4,1,1,-10), (1,5,3,-34,4,-3,23), \\ (-2,-2,2,4,-2,1,5), (3,6,0,-30,6,-7,8), \\ (0,0,1,0,0,0,0), (0,0,0,1,0,0,0), \\ (0,0,0,0,0,0,1) \} \text{.} \end{split} \end{equation*}

32.

\(V = \matrixring_{2 \times 2}(\R) \)
\(S = \left\{ \begin{abmatrix}{rr} 4 \amp 3 \\ 3 \amp -4 \end{abmatrix}, \begin{abmatrix}{rr} 3 \amp 3 \\ 4 \amp -2 \end{abmatrix} \right\}\)
Solution.
Use the entries of the matrices (that is, the coordinates relative to the standard basis of \(V \)) as row vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 4 \amp 3 \amp 3 \amp -4 \\ 3 \amp 3 \amp 4 \amp -2 \end{abmatrix} \qquad \rowredarrow \qquad \begin{bmatrix} 1 \amp 0 \amp -1 \amp -2 \\ 0 \amp 1 \amp \frac{7}{3} \amp \frac{4}{3} \end{bmatrix} \end{equation*}
The reduced vectors exhibit independence in the first and second components. Using the standard basis of \(V \text{,}\) we can interpret this as independence in the \((1,1) \) and \((1,2) \) entries of a \(2 \times 2 \) matrix, implying that we can extend to a basis by β€œfilling in” the \((2,1) \) and \((2,2) \) entries:
\begin{equation*} \matrixring_{2 \times 2}(\R) = \Span \left\{ \begin{abmatrix}{rr} 4 \amp 3 \\ 3 \amp -4 \end{abmatrix}, \begin{abmatrix}{rr} 3 \amp 3 \\ 4 \amp -2 \end{abmatrix} \begin{bmatrix} 0 \amp 0 \\ 1 \amp 0 \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \\ 0 \amp 1 \end{bmatrix} \right\}\text{.} \end{equation*}

33.

\(V = \matrixring_{2 \times 3}(\R) \)
\(S = \left\{ \begin{abmatrix}{rrr} -1 \amp -1 \amp 1 \\ -3 \amp 3 \amp 0 \end{abmatrix}, \begin{abmatrix}{rrr} 1 \amp 1 \amp -1 \\ 0 \amp -1 \amp -6 \end{abmatrix}, \begin{abmatrix}{rrr} 2 \amp 2 \amp -3 \\ -1 \amp 0 \amp -6 \end{abmatrix} \right\}\)
Solution.
Use the entries of the matrices (that is, the coordinates relative to the standard basis of \(V \)) as row vectors in a matrix and reduce.
\begin{equation*} \begin{split} \amp \begin{abmatrix}{rrrrrr} -1 \amp -1 \amp 1 \amp -3 \amp 3 \amp 0 \\ 1 \amp 1 \amp -1 \amp 0 \amp -1 \amp -6 \\ 2 \amp 2 \amp -3 \amp -1 \amp 0 \amp -6 \end{abmatrix} \\ \amp \rowredarrow \qquad \begin{abmatrix}{rrrrrr} 1 \amp 1 \amp 0 \amp 0 \amp -\frac{7}{3} \amp -14 \\ 0 \amp 0 \amp 1 \amp 0 \amp -\frac{4}{3} \amp - 8 \\ 0 \amp 0 \amp 0 \amp 1 \amp -\frac{2}{3} \amp 2 \end{abmatrix} \end{split} \end{equation*}
The reduced vectors exhibit independence in the first, third, and fourth components. Using the standard basis of \(V \text{,}\) we can interpret this as independence in \((1,1) \text{,}\) \((1,3) \text{,}\) and \((2,1) \) entries of a \(2 \times 3 \) matrix, implying that we can extend to a basis by β€œfilling in” the \((1,2) \text{,}\) \((2,2) \text{,}\) and \((2,3) \) entries:
\begin{equation*} \begin{split} \matrixring_{2 \times 2}(\R) = \Span \left\{ \begin{abmatrix}{rrr} -1 \amp -1 \amp 1 \\ -3 \amp 3 \amp 0 \end{abmatrix}, \begin{abmatrix}{rrr} 1 \amp 1 \amp -1 \\ 0 \amp -1 \amp -6 \end{abmatrix}, \begin{abmatrix}{rrr} 2 \amp 2 \amp -3 \\ -1 \amp 0 \amp -6 \end{abmatrix} \right. \\ \left. \begin{bmatrix} 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \end{bmatrix}, \begin{bmatrix} 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 1 \end{bmatrix} \right\} \end{split}\text{.} \end{equation*}

34.

\(V = \poly_3(\R) \)
\(S = \{ x + 3 x^2 + x^3, 2 x + 7 x^2 - x^3 \} \)
Solution.
Use the coefficients of the polynomials (that is, the coordinates relative to the standard basis of \(V \)) as row vectors in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 0 \amp 1 \amp 3 \amp -1 \\ 0 \amp 2 \amp 7 \amp -1 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrr} 0 \amp 1 \amp 0 \amp -4 \\ 0 \amp 0 \amp 1 \amp 1 \end{abmatrix} \end{equation*}
The reduced vectors exhibit independence in the second and third components. Using the standard basis of \(V \text{,}\) we can interpret this as independence in the \(x \) and \(x^2 \) β€œdirections”, implying that we can extend to a basis by β€œfilling in” the constant and \(x^3 \) β€œdirections”:
\begin{equation*} \poly_3(\R) = \Span \{ x + 3 x^2 + x^3, 2 x + 7 x^2 - x^3, 1, x^3 \} \text{.} \end{equation*}

35.

\(V = \poly_5(\R) \)
\begin{equation*} \begin{split} S = \{ -1 + 5 x - x^2 + x^4 + 6 x^5, 2 - 10 x + 3 x^2 - x^3 - 5 x^4 - 16 x^5, \\ -2 + 10 x - 3 x^2 + x^3 + 6 x^4 + 16 x^5 \} \end{split} \end{equation*}
Solution.
Use the coefficients of the polynomials (that is, the coordinates relative to the standard basis of \(V \)) as row vectors in a matrix and reduce.
\begin{align*} \amp \begin{abmatrix}{rrrrrr} -1 \amp 5 \amp -1 \amp 0 \amp 1 \amp 6 \\ 2 \amp -10 \amp 3 \amp -1 \amp -5 \amp -16 \\ -2 \amp 10 \amp -3 \amp 1 \amp 6 \amp 16 \end{abmatrix}\\ \amp \rowredarrow \qquad \begin{abmatrix}{rrrrrr} 1 \amp -5 \amp 0 \amp 1 \amp 0 \amp -2 \\ 0 \amp 0 \amp 1 \amp -1 \amp 0 \amp -4 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 0 \end{abmatrix} \end{align*}
The reduced vectors exhibit independence in the first, third, and fifth components. Using the standard basis of \(V \text{,}\) we can interpret this as independence in the constant, \(x^2 \) and \(x^4 \) β€œdirections”, implying that we can extend to a basis by β€œfilling in” the \(x \text{,}\) \(x^3 \text{,}\) and \(x^5 \) β€œdirections”:
\begin{equation*} \begin{split} \poly_5(\R) = \Span \{ \amp -1 + 5 x - x^2 + x^4 + 6 x^5, \\ \amp 2 - 10 x + 3 x^2 - x^3 - 5 x^4 - 16 x^5, \\ \amp -2 + 10 x - 3 x^2 + x^3 + 6 x^4 + 16 x^5, \\ \amp x, x^3, x^5 \} \text{.} \end{split} \end{equation*}

Testing for independence.

In each of the following, a set of vectors \(S \) in a vector space \(V \) is provided.
  1. Use ProcedureΒ 20.3.4 to test the vectors for independence.
  2. If the vectors are linearly dependent, express all dependence relations revealed in partΒ a.

36.

\(V = \R^5 \)
\(S = \{ (1, -4, 2, 6, -2), (0, -3, 3, 7, -7), (2, -5, 2, 3, -5) \} \)
Solution.
Use the vectors as columns in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrr} 1 \amp 0 \amp 2 \\ -4 \amp -3 \amp -5 \\ 2 \amp 3 \amp 2 \\ 6 \amp 7 \amp 3 \\ -2 \amp -7 \amp -5 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrr} 1 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
The rank is \(3 \text{,}\) which matches the number of vectors in \(S \text{.}\) Therefore, \(S \) is a linearly independent set.

37.

\(V = \matrixring_{2 \times 2}(\R) \)
\(S = \left\{ \begin{bmatrix} 2 \amp 1 \\ 0 \amp 1 \end{bmatrix}, \begin{abmatrix}{rr} 7 \amp 1 \\ -2 \amp 3 \end{abmatrix}, \begin{bmatrix} 5 \amp 3 \\ 0 \amp 2 \end{bmatrix}, \begin{bmatrix} 8 \amp 9 \\ 2 \amp 2 \end{bmatrix} \right\}\)
Solution.
Use the coordinate vectors of the vectors relative to the standard basis of \(\matrixring_{2 \times 2}(\R) \) as columns in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 2 \amp 7 \amp 5 \amp 8 \\ 1 \amp 1 \amp 3 \amp 9 \\ 0 \amp -2 \amp 0 \amp 2 \\ 1 \amp 3 \amp 2 \amp 2 \end{abmatrix} \qquad \rowredarrow \qquad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 0 \amp -5 \\ 0 \amp 1 \amp 0 \amp -1 \\ 0 \amp 0 \amp 1 \amp 5 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{equation*}
The rank is \(3 \text{,}\) which is less than the number of vectors in \(S \text{.}\) Therefore, \(S \) is a linearly dependent set.

38.

\(V = \poly_4(\R) \)
\begin{equation*} \begin{split} S = \{ x^4 + x^3 - 2 x^2 - x, x^4 - 2 x^2 + x + 3, x^4 + x^3 - x^2 + 1, \\ 5 x^4 + 4 x^3 - 6 x^2 + 4 \} \end{split} \end{equation*}
Solution.
Use the coordinate vectors of the vectors relative to the β€œreverse” standard basis \(\{ x^4, x^3, x^2, x, 1 \} \) of \(\poly_4(\R) \) as columns in a matrix and reduce.
\begin{equation*} \begin{abmatrix}{rrrr} 1 \amp 1 \amp 1 \amp 5 \\ 1 \amp 0 \amp 1 \amp 4 \\ -2 \amp -2 \amp -1 \amp -6 \\ -1 \amp 1 \amp 0 \amp 0 \\ 0 \amp 3 \amp 1 \amp 4 \end{abmatrix} \qquad \rowredarrow \qquad \begin{bmatrix} 1 \amp 0 \amp 0 \amp 0 \\ 0 \amp 1 \amp 0 \amp 0 \\ 0 \amp 0 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \\ 0 \amp 0 \amp 0 \amp 0 \end{bmatrix} \end{equation*}
The rank is \(4 \text{,}\) which matches the number of vectors in \(S \text{.}\) Therefore, \(S \) is a linearly independent set.

Determining equivalence of spans.

In each of the following, use CorollaryΒ 20.5.7 to determine whether \(\Span S_1 = \Span S_2 \text{.}\)

39.

\(S_1 = \{ (-2, -1, -6), (3, 1, 10), (4, 0, 16) \} \)
\(S_2 = \{ ( 4, 2, 12), (2, 1, 6), (3, 2, 8) \} \)
Solution.
Create matrices whose rows are the vectors in \(S_1, S_2 \text{,}\) respectively, and reduce.
\begin{gather*} S_1 \colon \quad \begin{abmatrix}{rrr} -2 \amp -1 \amp -6 \\ 3 \amp 1 \amp 10 \\ 4 \amp 0 \amp 16 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrr} 1 \amp 0 \amp 4 \\ 0 \amp 1 \amp -2 \\ 0 \amp 0 \amp 0 \end{abmatrix}\\ \\ S_2 \colon \quad \begin{bmatrix} 4 \amp 2 \amp 12 \\ 2 \amp 1 \amp 6 \\ 3 \amp 2 \amp 8 \end{bmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrr} 1 \amp 0 \amp 4 \\ 0 \amp 1 \amp -2 \\ 0 \amp 0 \amp 0 \end{abmatrix} \end{gather*}
Since the two matrices have the same RREF, they have the same row space. Therefore, \(\Span S_1 = \Span S_2 \text{.}\)

40.

\(S_1 = \{ (2, 1, -1, 3), (1, 0, 2, 3), (1, -1, 7, 5) \} \)
\(S_2 = \{ (1, 2, -6, 5), (0, 1, -4, 5), (2, 3, -8, 4) \} \)
Solution.
Create matrices whose rows are the vectors in \(S_1, S_2 \text{,}\) respectively, and reduce.
\begin{gather*} S_1 \colon \quad \begin{abmatrix}{rrrr} 2 \amp 1 \amp -1 \amp 3 \\ 1 \amp 0 \amp 2 \amp 3 \\ 1 \amp -1 \amp 7 \amp 5 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 2 \amp 0 \\ 0 \amp 1 \amp -5 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \end{abmatrix}\\ \\ S_2 \colon \quad \begin{abmatrix}{rrrr} 1 \amp 2 \amp -6 \amp 5 \\ 0 \amp 1 \amp -4 \amp 5 \\ 2 \amp 3 \amp -8 \amp 4 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 2 \amp 0 \\ 0 \amp 1 \amp -4 \amp 0 \\ 0 \amp 0 \amp 0 \amp 1 \end{abmatrix} \end{gather*}
Since the two matrices have different RREFs, they do not have the same row space. Therefore, \(\Span S_1 \neq \Span S_2 \text{.}\)

41.

\(S_1 = \left\{ \begin{abmatrix}{rr} 3 \amp 2 \\ -4 \amp - 8 \end{abmatrix}, \begin{abmatrix}{rr} 3 \amp 1 \\ -5 \amp -13 \end{abmatrix}, \begin{abmatrix}{rr} 2 \amp 2 \\ -2 \amp - 2 \end{abmatrix}, \begin{abmatrix}{rr} -2 \amp 0 \\ 4 \amp 12 \end{abmatrix} \right\}\)
\(S_2 = \left\{ \begin{bmatrix} 2 \amp 1 \\ 0 \amp 4 \end{bmatrix}, \begin{abmatrix}{rr} 1 \amp 2 \\ -3 \amp -7 \end{abmatrix}, \begin{abmatrix}{rr} 3 \amp 2 \\ -1 \amp 3 \end{abmatrix}, \begin{abmatrix}{rr} 1 \amp 1 \\ -1 \amp -1 \end{abmatrix} \right\}\)
Solution.
Create matrices whose rows are the coordinate vectors of the vectors in \(S_1, S_2 \text{,}\) respectively, relative to the standard basis for \(\matrixring_{2 \times 2}(\R) \text{,}\) and reduce.
\begin{gather*} S_1 \colon \quad \begin{abmatrix}{rrrr} 3 \amp 2 \amp -4 \amp - 8 \\ 3 \amp 1 \amp -5 \amp -13 \\ 2 \amp 2 \amp -2 \amp - 2 \\ -2 \amp 0 \amp 4 \amp 12 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp -2 \amp -6 \\ 0 \amp 1 \amp 1 \amp 5 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix}\\ \\ S_2 \colon \quad \begin{abmatrix}{rrrr} 2 \amp 1 \amp 0 \amp 4 \\ 1 \amp 2 \amp -3 \amp -7 \\ 3 \amp 2 \amp -1 \amp 3 \\ 1 \amp 1 \amp -1 \amp -1 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 1 \amp 5 \\ 0 \amp 1 \amp -2 \amp -6 \\ 0 \amp 0 \amp 0 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{gather*}
Since the two matrices have different RREFs, they do not have the same row space. Therefore, \(\Span S_1 \neq \Span S_2 \text{.}\)

42.

\(S_1 = \left\{ \begin{abmatrix}{rr} 1 \amp 0 \\ -3 \amp 12 \\ -1 \amp 5 \end{abmatrix}, \begin{abmatrix}{rr} 2 \amp 0 \\ 1 \amp 10 \\ 0 \amp -1 \end{abmatrix}, \begin{abmatrix}{rr} 2 \amp 0 \\ 0 \amp 12 \\ -1 \amp -3 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 0 \\ -1 \amp 2 \\ 0 \amp 3 \end{abmatrix} \right\}\)
\(S_2 = \left\{ \begin{abmatrix}{rr} 1 \amp 0 \\ -1 \amp 8 \\ -5 \amp -21 \end{abmatrix}, \begin{abmatrix}{rr} 1 \amp 0 \\ 0 \amp 6 \\ 1 \amp 6 \end{abmatrix}, \begin{abmatrix}{rr} -2 \amp 0 \\ 1 \amp -14 \\ 1 \amp 0 \end{abmatrix}, \begin{abmatrix}{rr} 0 \amp 0 \\ 0 \amp 0 \\ -2 \amp -10 \end{abmatrix} \right\}\)
Solution.
Create matrices whose rows are the coordinate vectors of the vectors in \(S_1, S_2 \text{,}\) respectively, relative to the standard basis for \(\matrixring_{3 \times 2}(\R) \text{,}\) and reduce.
\begin{gather*} \begin{split} S_1 \colon \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp -3 \amp 12 \amp -1 \amp 5 \\ 2 \amp 0 \amp 1 \amp 10 \amp 0 \amp -1 \\ 2 \amp 0 \amp 0 \amp 12 \amp -1 \amp -3 \\ 0 \amp 0 \amp -1 \amp 2 \amp 0 \amp 3 \end{abmatrix} \\ \qquad\qquad \rowredarrow \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp 0 \amp 6 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp -2 \amp 0 \amp -3 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 5 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{split}\\ \\ \begin{split} S_2 \colon \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp -1 \amp 8 \amp -5 \amp -21 \\ 1 \amp 0 \amp 0 \amp 6 \amp 1 \amp 6 \\ -2 \amp 0 \amp 1 \amp -14 \amp 1 \amp 0 \\ 0 \amp 0 \amp 0 \amp 0 \amp -2 \amp -10 \end{abmatrix} \\ \qquad\qquad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 0 \amp 6 \amp 0 \amp 1 \\ 0 \amp 0 \amp 1 \amp -2 \amp 0 \amp -3 \\ 0 \amp 0 \amp 0 \amp 0 \amp 1 \amp 5 \\ 0 \amp 0 \amp 0 \amp 0 \amp 0 \amp 0 \end{abmatrix} \end{split} \end{gather*}
Since the two matrices have the same RREF, they have the same row space. Therefore, \(\Span S_1 = \Span S_2 \text{.}\)

43.

\(S_1 = \{ x^3 + 2 x^2 - 6, 2 x^3 + 3 x^2 - 7, x^3 + 2 x^2 + x - 8 \}\)
\(S_2 = \{ 2 x^3 + x^2 + x + 1, x^3 + 4, x^3 - x + 6 \}\)
Solution.
The polynomials are all degree \(3 \text{,}\) so we will work in \(\poly_3(\R) \text{.}\) Create matrices whose rows are the coordinate vectors of the vectors in \(S_1, S_2 \text{,}\) respectively, relative to one of the standard bases for \(\poly_3(\R) \text{,}\) and reduce. We will opt to use the β€œreverse” standard basis \(\basisfont{S} = \{ x^3, x^2, x, 1 \} \text{,}\) since most of the polynomials in \(S_1 \) and \(S_2 \) are monic.
\begin{gather*} S_1 \colon \quad \begin{abmatrix}{rrrr} 1 \amp 2 \amp 0 \amp -6 \\ 2 \amp 3 \amp 0 \amp -7 \\ 1 \amp 2 \amp 1 \amp -8 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 0 \amp 4 \\ 0 \amp 1 \amp 0 \amp -5 \\ 0 \amp 0 \amp 1 \amp -2 \end{abmatrix}\\ \\ S_2 \colon \quad \begin{abmatrix}{rrrr} 2 \amp 1 \amp 1 \amp 1 \\ 1 \amp 0 \amp 0 \amp 4 \\ 1 \amp 0 \amp -1 \amp 6 \end{abmatrix} \quad \rowredarrow \quad \begin{abmatrix}{rrrr} 1 \amp 0 \amp 0 \amp 4 \\ 0 \amp 1 \amp 0 \amp -5 \\ 0 \amp 0 \amp 1 \amp -2 \end{abmatrix} \end{gather*}
Since the two matrices have the same RREF, they have the same row space. Therefore, \(\Span S_1 = \Span S_2 \text{.}\)

44.

\begin{gather*} \begin{split} S_1 = \{ \amp x^5 + x^3 + 7 x - 11, x^5 - x^4 + 2 x^2 - 9 x - 4, \\ \amp x^5 + 3 x^2 - 12 x, x^5 + 4 x^2 - 17 x + 2 \} \end{split}\\ \\ \begin{split} S_2 = \{ \amp x^5 - x^4 - x^3 + x^2 - 10 x + 4, x^3 + 2 x^2 - 6 x - 1, \\ \amp 2 x^5 - 3 x^4 - 7 x^3 - 3 x^2 - 7 x + 11, 2 x^3 + 3 x^2 - 7 x - 4 \} \end{split} \end{gather*}
Solution.
The polynomials are all degree \(5 \) or less, so we will work in \(\poly_5(\R) \text{.}\) Create matrices whose rows are the coordinate vectors of the vectors in \(S_1, S_2 \text{,}\) respectively, relative to one of the standard bases for \(\poly_5(\R) \text{,}\) and reduce. We will opt to use the β€œreverse” standard basis \(\basisfont{S} = \{ x^5, x^4, x^3, x^2, x, 1 \} \text{,}\) since many of the polynomials in \(S_1 \) and \(S_2 \) are monic.
\begin{gather*} \begin{split} S_1 \colon \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp 1 \amp 0 \amp 7 \amp -11 \\ 1 \amp -1 \amp 0 \amp 2 \amp - 9 \amp -4 \\ 1 \amp 0 \amp 0 \amp 3 \amp -12 \amp 0 \\ 1 \amp 0 \amp 0 \amp 4 \amp -17 \amp 2 \end{abmatrix} \\ \qquad\qquad \rowredarrow \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp 0 \amp 0 \amp 3 \amp -6 \\ 0 \amp 1 \amp 0 \amp 0 \amp 2 \amp 2 \\ 0 \amp 0 \amp 1 \amp 0 \amp 4 \amp -5 \\ 0 \amp 0 \amp 0 \amp 1 \amp -5 \amp 2 \end{abmatrix} \end{split}\\ \\ \begin{split} S_2 \colon \quad \begin{abmatrix}{rrrrrr} 1 \amp -1 \amp -2 \amp 1 \amp -10 \amp 4 \\ 0 \amp 0 \amp 1 \amp 2 \amp - 6 \amp -1 \\ 2 \amp -3 \amp -7 \amp -3 \amp - 7 \amp 11 \\ 0 \amp 0 \amp 2 \amp 3 \amp - 7 \amp -4 \end{abmatrix} \\ \qquad\qquad \rowredarrow \quad \begin{abmatrix}{rrrrrr} 1 \amp 0 \amp 0 \amp 0 \amp 3 \amp -6 \\ 0 \amp 1 \amp 0 \amp 0 \amp 0 \amp 2 \\ 0 \amp 0 \amp 1 \amp 0 \amp 4 \amp -5 \\ 0 \amp 0 \amp 0 \amp 1 \amp -5 \amp 2 \end{abmatrix} \end{split} \end{gather*}
Since the two matrices have different RREFs, they do not have the same row space. Therefore, \(\Span S_1 \neq \Span S_2 \text{.}\)

Inverse null space problem.

In RemarkΒ 16.4.9 we made the claim that every subspace is somehow defined by a homogeneous condition or a set of homogeneous conditions. In each of the following, a spanning set for a subspace \(W \) of a vector space \(V \) is provided. Determine a homogeneous system with solution space precisely \(W \text{.}\)

45.

\(V \) and \(W \) from ExerciseΒ 27.
Solution.
In the solution to ExerciseΒ 27, we determined a simplified basis for \(W \text{:}\)
\begin{equation*} W = \Span \{ (1,0,0,2,-1), (0,1,0,1,-2), (0,0,1,-3,5) \} \text{.} \end{equation*}
So every vector \(\uvec{x} = (x_1,x_2,x_3,x_4,x_5) \) in \(W \) is somehow a linear combination of these basis vectors:
\begin{equation*} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \\ x_4 \\ x_5 \end{bmatrix} = r \begin{abmatrix}{r} 1 \\ 0 \\ 0 \\ 2 \\ -1 \end{abmatrix} + s \begin{abmatrix}{r} 0 \\ 1 \\ 0 \\ 1 \\ -2 \end{abmatrix} + t \begin{abmatrix}{r} 0 \\ 0 \\ 1 \\ -3 \\ 5 \end{abmatrix}\text{.} \end{equation*}
Working as if reversing the process of calculating a basis for a null space, calculate the linear combination on the right and compare entries on either side of the equality to create parametric expressions for the components of \(\uvec{x} \text{.}\)
\begin{align*} x_1 \amp = r \\ x_2 \amp = s \\ x_3 \amp = t \\ x_4 \amp = 2 r + s - 3 t \\ x_5 \amp = - r - 2 s + 5 t \end{align*}
Continuing to reverse the null-space-basis procedure, in the two expressions that are not merely parameter assignments, replace the parameters with the corresponding components and rearrange to become a homogeneous system.
\begin{equation*} \begin{sysofeqns}{rcrcrcrcr} 2 x_1 \amp + \amp x_2 \amp - \amp 3 x_3 \amp - \amp x_4 \amp = \amp 0 \\ x_1 \amp + \amp 2 x_2 \amp - \amp 5 x_3 \amp + \amp x_5 \amp = \amp 0 \end{sysofeqns} \end{equation*}
(Note that in the \(x_4 \) parametric expression we chose to subtract \(x_4 \) to the right-hand side, whereas in the \(x_5 \) parametric expression we chose to subtract the entire parametric expression to the left-hand side.)
Thus \(W \) is precisely the solution space to the homogeneous system above. You may verify that each of the original spanning vectors for \(W \) provided in ExerciseΒ 27 lies in this solution space.

46.

\(V \) and \(W \) from ExerciseΒ 28.
Solution.
Let \(W' \) be the corresponding subspace of \(\R^6 \text{,}\) spanned by the coordinate vectors of the provided spanning vectors for \(W \text{,}\) relative to the standard basis of \(\matrixring_{2 \times 3}(\R) \text{.}\) In the solution to ExerciseΒ 28, we determined a simplified basis for \(W' \text{:}\)
\begin{equation*} \begin{split} W = \Span \left\{ \left( 1, 0, 0, 0, -\tfrac{15}{2}, -\tfrac{71}{2} \right), \left( 0, 1, 0, 0, -\tfrac{ 9}{2}, -\tfrac{97}{6} \right), \\ \left( 0, 0, 1, 0, \tfrac{ 1}{2}, \tfrac{ 1}{2} \right), \left( 0, 0, 0, 1, \tfrac{ 3}{2}, \tfrac{35}{6} \right) \right\} \end{split}\text{.} \end{equation*}
So every vector \(\uvec{x} = (x_1,x_2,x_3,x_4,x_5,x_6) \) in \(W' \) is somehow a linear combination of these basis vectors:
\begin{equation*} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \\ x_4 \\ x_5 \\ x_6 \end{bmatrix} = r \begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \\ -\frac{15}{2} \\ -\frac{71}{2} \end{bmatrix} + s \begin{bmatrix} 0 \\ 1 \\ 0 \\ 0 \\ -\frac{ 9}{2} \\ -\frac{97}{6} \end{bmatrix} + t \begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \\ \frac{ 1}{2} \\ \frac{ 1}{2} \end{bmatrix} + u \begin{bmatrix} 0 \\ 0 \\ 0 \\ 1 \\ \frac{ 3}{2} \\ \frac{35}{6} \end{bmatrix}\text{.} \end{equation*}
Working as if reversing the process of calculating a basis for a null space, calculate the linear combination on the right and compare entries on either side of the equality to create parametric expressions for the components of \(\uvec{x} \text{.}\)
\begin{align*} x_1 \amp = r \\ x_2 \amp = s \\ x_3 \amp = t \\ x_4 \amp = u \\ x_5 \amp = -\tfrac{15}{2} \, r - \tfrac{ 9}{2} \, s + \tfrac{1}{2} \, t + \tfrac{ 3}{2} \, u \\ x_6 \amp = -\tfrac{71}{2} \, r - \tfrac{97}{6} \, s + \tfrac{1}{2} \, t + \tfrac{35}{6} \, u \end{align*}
Continuing to reverse the null-space-basis procedure, in the two expressions that are not merely parameter assignments, replace the parameters with the corresponding components and rearrange to become a homogeneous system.
\begin{equation*} \begin{sysofeqns}{rcrcrcrcrcr} 15 x_1 \amp + \amp 9 x_2 \amp - \amp x_3 \amp - \amp 3 x_4 \amp + \amp 2 x_5 \amp = \amp 0 \\ 213 x_1 \amp + \amp 97 x_2 \amp - \amp 3 x_3 \amp - \amp 35 x_4 \amp + \amp 6 x_6 \amp = \amp 0 \end{sysofeqns} \end{equation*}
(Note that we have cleared fractions by multiplying each equation through by a common denominator.)
To translate this from \(\R^6 \) back to \(\matrixring_{2 \times 3}(\R) \text{,}\) replace the component variables with matrix entry variables, consistent with how matrix entries become coordinates relative to the standard basis of \(\matrixring_{2 \times 3}(\R) \text{.}\)
\begin{equation*} \begin{sysofeqns}{rcrcrcrcrcr} 15 a_{11} \amp + \amp 9 a_{12} \amp - \amp a_{13} \amp - \amp 3 a_{21} \amp + \amp 2 a_{22} \amp = \amp 0 \\ 213 a_{11} \amp + \amp 97 a_{12} \amp - \amp 3 a_{13} \amp - \amp 35 a_{21} \amp + \amp 6 a_{23} \amp = \amp 0 \end{sysofeqns} \end{equation*}
That is, \(W \) consists precisely of those \(2 \times 3 \) matrices \(A = \begin{bmatrix} a_{ij} \end{bmatrix} \) whose entries represent solutions to the homogeneous system above. You may verify that each of the original spanning vectors for \(W \) provided in ExerciseΒ 28 represent such solutions.

47.

\(V \) and \(W \) from ExerciseΒ 29.
Solution.
Let \(W' \) be the corresponding subspace of \(\R^5 \text{,}\) spanned by the coordinate vectors of the provided spanning vectors for \(W \text{,}\) relative to the β€œreversed” standard basis \(\{ x^4, x^3, x^2, x, 1 \} \) of \(\poly_4(\R) \text{.}\) In the solution to ExerciseΒ 29, we determined a simplified basis for \(W' \text{:}\)
\begin{equation*} W = \Span \left\{ \left( 1, 0, 0, 0, -\tfrac{1}{4} \right), \left( 0, 1, 0, 0, -\tfrac{1}{2} \right), \left( 0, 0, 1, 0, \tfrac{7}{4} \right), \left( 0, 0, 0, 1, \tfrac{5}{4} \right) \right\}\text{.} \end{equation*}
So every vector \(\uvec{x} = (x_1,x_2,x_3,x_4,x_5) \) in \(W' \) is somehow a linear combination of these basis vectors:
\begin{equation*} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \\ x_4 \\ x_5 \end{bmatrix} = r \begin{bmatrix} 1 \\ 0 \\ 0 \\ 0 \\ -\frac{1}{4} \end{bmatrix} + s \begin{bmatrix} 0 \\ 1 \\ 0 \\ 0 \\ -\frac{1}{2} \end{bmatrix} + t \begin{bmatrix} 0 \\ 0 \\ 1 \\ 0 \\ \frac{7}{4} \end{bmatrix} + u \begin{bmatrix} 0 \\ 0 \\ 0 \\ 1 \\ \frac{5}{4} \end{bmatrix}\text{.} \end{equation*}
Working as if reversing the process of calculating a basis for a null space, calculate the linear combination on the right and compare entries on either side of the equality to create parametric expressions for the components of \(\uvec{x} \text{.}\)
\begin{align*} x_1 \amp = r \\ x_2 \amp = s \\ x_3 \amp = t \\ x_4 \amp = u \\ x_5 \amp = -\tfrac{1}{4} \, r - \tfrac{1}{2} \, s + \tfrac{7}{4} \, t + \tfrac{5}{4} \, u \end{align*}
Continuing to reverse the null-space-basis procedure, in the parametric expression for \(x_5 \) (the only one that is not merely a parameter assignment), replace the parameters with the corresponding components and rearrange to become a homogeneous system.
\begin{equation*} \begin{sysofeqns}{rcrcrcrcrcr} x_1 \amp + \amp 2 x_2 \amp - \amp 7 x_3 \amp - \amp 5 x_4 \amp + \amp 4 x_5 \amp = \amp 0 \end{sysofeqns} \end{equation*}
(Note that we have cleared fractions by multiplying through by common denominator \(4 \text{.}\))
To translate this from \(\R^5 \) back to \(\poly_4(\R) \text{,}\) replace the component variables with polynomial coefficient variables, consistent with how polynomial coefficients become coordinates relative to the (reverse) standard basis of \(\poly_4(\R) \text{.}\)
\begin{equation*} \begin{sysofeqns}{rcrcrcrcrcr} a_4 \amp + \amp 2 a_3 \amp - \amp 7 a_2 \amp - \amp 5 a_1 \amp + \amp 4 a_0 \amp = \amp 0 \end{sysofeqns} \end{equation*}
That is, \(W \) consists precisely of those degree-\(4 \) polynomials
\begin{equation*} \uvec{p}(x) = a_4 x^4 + a_3 x^3 + a_2 x^2 + a_1 x + a_0 \end{equation*}
whose coefficients represent solutions to the homogeneous system above. You may verify that each of the original spanning vectors for \(W \) provided in ExerciseΒ 29 represent such solutions.