Sava's question via email about matrix multiplication

In summary, we evaluated $\displaystyle \begin{align*} A\,A^T \end{align*}$ and $\displaystyle \begin{align*} A^T\,A \end{align*}$ for the given matrix $\displaystyle \begin{align*} A \end{align*}$ and found that they both result in $\displaystyle \begin{align*} 25\,I \end{align*}$. This suggests that $\displaystyle \begin{align*} A^{-1} = \frac{1}{25}\,A^T \end{align*}$, but this should be verified by checking $\displaystyle \begin{align*} A^
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Given the matrix $\displaystyle \begin{align*} A = \left[ \begin{matrix} 3 & 0 & -4 \\ 4 & 0 & \phantom{-}3 \\ 0 & 5 & \phantom{-}0 \end{matrix}\right] \end{align*}$ evaluate $\displaystyle \begin{align*} A\,A^T \end{align*}$ and $\displaystyle \begin{align*} A^T\,A \end{align*}$. Hence write down $\displaystyle \begin{align*} A^{-1} \end{align*}$.

$\displaystyle \begin{align*} A\,A^T &= \left[\begin{matrix} 3 & 0 & -4 \\ 4 & 0 & \phantom{-}3 \\ 0 & 5 & \phantom{-}0 \end{matrix}\right]\left[ \begin{matrix} \phantom{-}3 & 4 & 0 \\ \phantom{-}0 & 0 & 5 \\ -4 & 3 & 0 \end{matrix}\right] \\ &= \left[ \begin{matrix} 3\cdot 3 + 0 \cdot 0 + \left( -4 \right) \cdot \left( -4 \right) & 3 \cdot 4 + 0 \cdot 0 + \left( -4 \right) \cdot 3 & 3 \cdot 0 + 0 \cdot 5 + \left( -4 \right) \cdot 0 \\ 4 \cdot 3 + 0 \cdot 0 + 3 \cdot \left( -4 \right) & 4 \cdot 4 + 0 \cdot 0 + 3 \cdot 3 & 4\cdot 0 + 0 \cdot 5 + 3 \cdot 0 \\ 0 \cdot 3 + 5 \cdot 0 + 0 \cdot \left( -4 \right) & 0 \cdot 4 + 5 \cdot 0 + 0 \cdot 3 & 0 \cdot 0 + 5 \cdot 5 + 0 \cdot 0 \end{matrix} \right] \\ &= \left[ \begin{matrix} 25 & 0 & 0 \\ 0 & 25 & 0 \\ 0 & 0 & 25 \end{matrix} \right] \\ &= 25\,I \end{align*}$

Since post-multiplying $\displaystyle \begin{align*} A \end{align*}$ by $\displaystyle \begin{align*} A^T \end{align*}$ gave $\displaystyle \begin{align*} 25\,I \end{align*}$, it suggests that $\displaystyle \begin{align*} A^{-1} = \frac{1}{25}\,A^T \end{align*}$.

Of course, we must also check that $\displaystyle \begin{align*} A^T\,A = 25\,I \end{align*}$ as well. This can be left to the OP/Reader. IF this is the case, then $\displaystyle \begin{align*} A^{-1} = \frac{1}{25}\,A^T \end{align*}$.
 
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1. What is matrix multiplication and why is it important in science?

Matrix multiplication is a mathematical operation that involves multiplying two matrices to produce a new matrix. It is important in science because it is used to represent and solve systems of linear equations, which are commonly used to model real-world phenomena in fields such as physics, engineering, and economics.

2. How do you perform matrix multiplication?

To multiply two matrices, the number of columns in the first matrix must match the number of rows in the second matrix. Then, for each element in the resulting matrix, you multiply the corresponding elements in the row of the first matrix by the column of the second matrix and add them together.

3. Can matrices of any size be multiplied together?

No, the number of columns in the first matrix must match the number of rows in the second matrix in order for matrix multiplication to be possible.

4. Is matrix multiplication commutative?

No, matrix multiplication is not commutative, which means that the order in which you multiply two matrices matters. In other words, A x B is not equal to B x A.

5. How is matrix multiplication used in data analysis and machine learning?

Matrix multiplication is used in data analysis and machine learning to perform operations such as data transformation, feature selection, and model training. It is also a fundamental tool in linear algebra, which is essential for understanding and working with many machine learning algorithms.

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