Finding the image, the kernel, their dimensions and their bases of a linear map - verify my solution I'm learning linear algebra and trying to find the image, the kernel, their dimensions and their bases of a linear map $ \varphi (a,b,c,d) = (3a+2b, b-c,2d-a) $. Also I'm supposed to find the matrix of the linear map in bases $B=$ {$(1,0,0,0),(1,1,0,0), (1,1,1,0), (1,1,1,1)$} and $C=$ {$(1,1,1), (0,1,1), (0,0,-1)$}.
My solution is this:
Created a matrix of the linear map and solved all linear equations for $0$.
$\begin{pmatrix}
 3  & 2  & 0 &0\\  
 0&1  &-1  &0 \\ 
 -1&0  &0  &2 
\end{pmatrix}$
$\sim $
$\begin{pmatrix}
 1  & 0  & 0 &2\\  
 0&1  &0  &3 \\ 
 0&0  &1  &3 
\end{pmatrix}$ $x1=2s$ ,  $x2 = -3s$ , $x3 = -3s$ , $x4=s$
Therefore the kernel of $ \varphi $ =  $<s*(2,-3,-3,1)>$ and $B_{ker}=(2,-3,-3,1)$ and the dimension of the kernel $=1$. Since it's $\mathbb{R}^4\rightarrow \mathbb{R}^3$, the dimension of image  has to be $3$. We have pivots in the first 3 colums, so we can say that  $<(3,0,-1),(2,1,0), (0,-1,0)>$ is the image of $ \varphi $. And for bases of $\varphi$, we can take $(3,0,−1),(2,1,0),(0,−1,0)$, as they are linearly independent.
Is my solution correct?
However, I don't know how to find the matrix in the bases B and C. Any help with that? Thanks!
 A: There are a couple of mistakes. First, the Reduced Row Echelon Form (RREF) of the matrix should be
\begin{equation}
\begin{pmatrix}
 1  & 0 & 0 & -2 \\  
 0 & 1 & 0 & 3 \\ 
 0 & 0 & 1 & 3 
\end{pmatrix}
\end{equation}
It should be $-2$ in the corner, not $2$. But surprisingly, the basis for $\ker (\varphi)$ you found is actually correct (you must have made a second sign error in the computation which cancelled out with the first error). 

and the dimension of the kernel $=1$. Since it's $\mathbb{R^4} \to \mathbb{R^3}$, the dimension of image has to be $3$.

This is correct. 

We have pivots in the first $3$ colums, so we can say that $<(3,0,−1),(2,1,0),(0,−1,0)>$ is the image of $\varphi$. And for bases of $\varphi$, we can take $(3,0,−1),(2,1,0),(0,−1,0)$, as they are linearly independent.

This is an incorrect statement; this I think is more of a terminology mistake rather than a deep conceptual one. The proper statement is $\{(3,0,−1),(2,1,0),(0,−1,0)\}$ forms a basis for the image of $\varphi$. Recall that the image of a linear map is a subspace of $\mathbb{R^3}$, so it can't just consist of $3$ vectors, but a basis for a $3$-dimensional image consists of $3$ vectors.
By the way, for this particular example, there is a much easier way to determine a basis for the image of $\varphi$. You already mentioned that the image has dimension $3$. But notice that the target space $\mathbb{R^3}$ also has dimension $3$. Hence, $\text{image}(\varphi) = \mathbb{R^3}$. So there's a particularly obvious basis: $\{(1,0,0), (0,1,0), (0,0,1) \}$.

Lastly, to compute $[\varphi]_B^C$, the matrix of $\varphi$ with respect to the bases $B$ and $C$, what you have to do is for each vector $v \in B$, compute what $\varphi(v)$ is, and write it as a linear combination of vectors from $C$. The coefficients will then be the entries of the matrix
For example, the first vector in $B$ is $(1,0,0,0)$. So, now we have to evaluate $\varphi$ on this vector:
\begin{align}
\varphi(1,0,0,0) &= (1,0,-1) \\
&= (1,1,1) - (0,1,1) + (0,0,-1)
\end{align}
Notice that the coefficients are $1,-1,1$. So, the first column of $[\varphi]_B^C$ looks like 
\begin{pmatrix}
1 & \cdot & \cdot & \cdot\\
-1 & \cdot & \cdot & \cdot \\
1 & \cdot & \cdot & \cdot
\end{pmatrix}
The second vector of $B$ is $(1,1,0,0)$. Now, we compute again:
\begin{align}
\varphi(1,1,0,0) &= (5,1,-1) \\
&= 5 (1,1,1) -4 (0,1,1) + 2(0,0,-1)
\end{align}
So, the first two out of four columns of $[\varphi]_B^C$ look like:
\begin{equation}
\begin{pmatrix}
1 & 5 & \cdot & \cdot\\
-1 & -4 & \cdot & \cdot \\
1 & 2 & \cdot & \cdot
\end{pmatrix}
\end{equation}
I'll leave it to you to figure out what the last two columns are (follow the same process I did).
