Is matrix $A^TA$ always symmetric? Through experience, I've seen that the following statement holds true: "$A^TA$ is always a symmetric matrix?", where $A$ is any matrix. However can this statement be proven/falsified?
 A: Ideally we've already proved both $(A^T)^T=A$ and $(AB)^T=B^T A^T$. If not, prove these first. Then $(A^T A)^T=A^T (A^T)^T =A^TA$.
A: We know $(AB)^T=B^TA^T$, so $(A^TA)^T=A^T(A^T)^T=A^TA$ and hence $A^TA$ is always symmetric.
A: Another proof per element. Let $T$ be a transpose of $A$, meaning $A^T = T$. We want to proof that $R = AT$ is symmetric, i.e. $R_{i,j} = R_{j,i}$.

*

*We know that  $A$ has ($m\times n$) elements, and  $T$ has ($n\times m$) elements.


*Generally, a row of $A$ with an index ($k$) is the $k^{th}$ column of its transpose, $T$:
$$A_k^{row} = T_k^{col}$$


*Similarly, the $k^{th}$ column of $A$ is the $k^{th}$ row of its transpose:
$$A_k^{col} = T_k^{row}$$


*Per matrix multiplication, element $R_{i,j}$ is the dot product between the $i^{th}$ row of first matrix and the  $j^{th}$ column of the second matrix: $$\;\; R_{i,j}= A_i^{row} \cdot T_j^{col}$$


*And per equality in (2), the $T_j^{col}$ is the $A_j^{row}$:
$$ R_{i,j}= A_i^{row} \cdot A_j^{row}$$


*When switching indices
$$ R_{j,i}= A_j^{row} \cdot T_i^{col}$$


*According to (2) again, the $T_i^{col}$ is the $A_i^{row}$:
$$ R_{j,i}= A_j^{row} \cdot A_i^{row}$$


*From (5) and (7) we see that $R_{i,j} = R_{j,i}$ because dot product is commutative.
That also shows you a quick way to calculate a matrix multiplied by its transpose. Just calculate the dot product on the rows of the first matrix.
Example
$R = AA^T$
$$A = \begin{bmatrix}
1 & 3 & 5\\
4 & 2 & 0
\end{bmatrix}$$
To calculate $AA^T$, just calculate the dot product of the rows of the first matrix, $A$ here.

*

*$R_{1,1} = A_1^{row} \cdot A_1^{row} =  \begin{bmatrix}1 \\ 3 \\ 5\end{bmatrix} \cdot \begin{bmatrix}1 \\ 3 \\ 5\end{bmatrix} = [1 + 9 + 25] = [35] $

*$R_{1,2} = A_1^{row} \cdot A_2^{row} =  \begin{bmatrix}1 \\ 3 \\ 5\end{bmatrix} \cdot \begin{bmatrix}4 \\ 2 \\ 0\end{bmatrix} = [4 + 6 + 0] = [10] $

*$R_{2,1} = A_2^{row} \cdot A_1^{row} =  \begin{bmatrix}4 \\ 2 \\ 0\end{bmatrix} \cdot \begin{bmatrix}1 \\ 3 \\ 5\end{bmatrix} = [4 + 6 + 0] = [10] $

*$R_{2,2} = A_2^{row} \cdot A_2^{row} =  \begin{bmatrix}4 \\ 2 \\ 0\end{bmatrix} \cdot \begin{bmatrix}4 \\ 2 \\ 0\end{bmatrix} = [16 + 4 + 0] = [20] $
$$R = \begin{bmatrix}
35 & 10\\
10 & 20
\end{bmatrix}$$
$R = A^TA$
Do the same for rows of $A^T$, answer is below:
$$R = \begin{bmatrix}
17 & 11 & 5\\
11 & 13 & 15\\
5& 15 & 25\\
\end{bmatrix}$$
You can also apply the rule for the columns of the second matrix, doesn't matter.
