Basis of Span in Vector Space of Polynomials of Degree 2 or Less
Let $P_2$ be the vector space of all polynomials of degree $2$ or less with real coefficients.
Let
\[S=\{1+x+2x^2, \quad x+2x^2, \quad -1, \quad x^2\}\]
be the set of four vectors in $P_2$.
Then find a basis of the subspace $\Span(S)$ among the vectors in $S$.
(Linear […]

Find All Values of $x$ such that the Matrix is Invertible
Given any constants $a,b,c$ where $a\neq 0$, find all values of $x$ such that the matrix $A$ is invertible if
\[
A=
\begin{bmatrix}
1 & 0 & c \\
0 & a & -b \\
-1/a & x & x^{2}
\end{bmatrix}
.
\]
Solution.
We know that $A$ is invertible precisely when […]

Find All Values of $a$ which Will Guarantee that $A$ Has Eigenvalues 0, 3, and -3.
Let $A$ be the matrix given by
\[
A=
\begin{bmatrix}
-2 & 0 & 1 \\
-5 & 3 & a \\
4 & -2 & -1
\end{bmatrix}
\]
for some variable $a$. Find all values of $a$ which will guarantee that $A$ has eigenvalues $0$, $3$, and $-3$.
Solution.
Let $p(t)$ be the […]

Find a Spanning Set for the Vector Space of Skew-Symmetric Matrices
Let $W$ be the set of $3\times 3$ skew-symmetric matrices. Show that $W$ is a subspace of the vector space $V$ of all $3\times 3$ matrices. Then, exhibit a spanning set for $W$.
Proof.
To prove that $W$ is a subspace of $V$, the $3\times 3$ zero matrix […]

In which $\R^k$, are the Nullspace and Range Subspaces?
Let $A$ be an $m \times n$ matrix.
Suppose that the nullspace of $A$ is a plane in $\R^3$ and the range is spanned by a nonzero vector $\mathbf{v}$ in $\R^5$. Determine $m$ and $n$. Also, find the rank and nullity of $A$.
Solution.
For an $m \times n$ matrix $A$, the […]

Find a basis for $\Span(S)$, where $S$ is a Set of Four Vectors
Find a basis for $\Span(S)$ where $S=
\left\{
\begin{bmatrix}
1 \\ 2 \\ 1
\end{bmatrix}
,
\begin{bmatrix}
-1 \\ -2 \\ -1
\end{bmatrix}
,
\begin{bmatrix}
2 \\ 6 \\ -2
\end{bmatrix}
,
\begin{bmatrix}
1 \\ 1 \\ 3
\end{bmatrix}
\right\}$.
Solution.
We […]

Find a Basis for the Subspace spanned by Five Vectors
Let $S=\{\mathbf{v}_{1},\mathbf{v}_{2},\mathbf{v}_{3},\mathbf{v}_{4},\mathbf{v}_{5}\}$ where
\[
\mathbf{v}_{1}=
\begin{bmatrix}
1 \\ 2 \\ 2 \\ -1
\end{bmatrix}
,\;\mathbf{v}_{2}=
\begin{bmatrix}
1 \\ 3 \\ 1 \\ 1
\end{bmatrix}
,\;\mathbf{v}_{3}=
\begin{bmatrix}
1 \\ 5 \\ -1 […]