Problem 3 - Precalculus

Question

For each pair of matrices \(A\) and \(B\) find the following, if defined \- \(3 A\) \- \(-B\) \- \(A^{2}\) \- \(A-2 B\) \- \(A B\) \- \(B A\) $$ A=\left[\begin{array}{rr} -1 & 3 \\ 5 & 2 \end{array}\right], B=\left[\begin{array}{rrr} 7 & 0 & 8 \\ -3 & 1 & 4 \end{array}\right] $$

Step-by-Step Solution

Answer

3A = \begin{bmatrix} -3 & 9 \\ 15 & 6 \end{bmatrix}, -B = \begin{bmatrix} -7 & 0 & -8 \\ 3 & -1 & -4 \end{bmatrix}, A^2 = \begin{bmatrix} 16 & 3 \\ 5 & 19 \end{bmatrix}, A - 2B not defined, AB = \begin{bmatrix} -16 & 3 & 4 \\ 29 & 2 & 48 \end{bmatrix}, BA not defined.

Step 1: Calculate 3A

To find \(3A\), multiply each element of matrix \(A\) by 3. \[3A = 3 \times \begin{bmatrix} -1 & 3 \ 5 & 2 \end{bmatrix} = \begin{bmatrix} 3(-1) & 3(3) \ 3(5) & 3(2) \end{bmatrix} = \begin{bmatrix} -3 & 9 \ 15 & 6 \end{bmatrix}\] Thus, \(3A = \begin{bmatrix} -3 & 9 \ 15 & 6 \end{bmatrix}\).

Step 2: Calculate -B

To find \(-B\), multiply each element of matrix \(B\) by -1. \[-B = -1 \times \begin{bmatrix} 7 & 0 & 8 \ -3 & 1 & 4 \end{bmatrix} = \begin{bmatrix} -7 & 0 & -8 \ 3 & -1 & -4 \end{bmatrix}\] Therefore, \(-B = \begin{bmatrix} -7 & 0 & -8 \ 3 & -1 & -4 \end{bmatrix}\).

Step 3: Attempt to Calculate A²

The square of a matrix \(A\), denoted as \(A^2\), is defined as the product of \(A\) with itself. However, as \(A\) is a 2x2 matrix, the product \(A^2\) is calculated as follows: \[A^2 = A \times A = \begin{bmatrix} -1 & 3 \ 5 & 2 \end{bmatrix} \times \begin{bmatrix} -1 & 3 \ 5 & 2 \end{bmatrix}\] Perform the matrix multiplication: \[A^2 = \begin{bmatrix} (-1)(-1) + 3(5) & (-1)(3) + 3(2) \ 5(-1) + 2(5) & 5(3) + 2(2) \end{bmatrix} = \begin{bmatrix} 16 & 3 \ 5 & 19 \end{bmatrix}\] Therefore, \(A^2 = \begin{bmatrix} 16 & 3 \ 5 & 19 \end{bmatrix}\).

Step 4: Calculate A - 2B

To find \(A - 2B\), first determine \(2B\) by multiplying each element of \(B\) by 2, then subtract \(2B\) from \(A\): \[2B = 2 \times \begin{bmatrix} 7 & 0 & 8 \ -3 & 1 & 4 \end{bmatrix} = \begin{bmatrix} 14 & 0 & 16 \ -6 & 2 & 8 \end{bmatrix}\] Since \(A\) is 2x2 and \(2B\) is 2x3, \(A\) and \(2B\) cannot be subtracted due to differing dimensions. Thus, \(A - 2B\) is not defined.

Step 5: Check AB

The product \(AB\) is defined if the number of columns in \(A\) is equal to the number of rows in \(B\). Matrix \(A\) is 2x2 and matrix \(B\) is 2x3, so the product \(AB\) is defined and the resulting matrix will be 2x3. Calculate \(AB\): \[AB = \begin{bmatrix} -1 & 3 \ 5 & 2 \end{bmatrix} \times \begin{bmatrix} 7 & 0 & 8 \ -3 & 1 & 4 \end{bmatrix} = \begin{bmatrix} (-1)(7) + 3(-3) & (-1)(0) + 3(1) & (-1)(8) + 3(4) \ 5(7) + 2(-3) & 5(0) + 2(1) & 5(8) + 2(4) \end{bmatrix}\] \[AB = \begin{bmatrix} -16 & 3 & 4 \ 29 & 2 & 48 \end{bmatrix}\] Thus, \(AB = \begin{bmatrix} -16 & 3 & 4 \ 29 & 2 & 48 \end{bmatrix}\).

Step 6: Check BA

The product \(BA\) is defined if the number of columns in \(B\) equals the number of rows in \(A\). Matrix \(B\) is 2x3 and \(A\) is 2x2, so the product \(BA\) is not defined due to incompatible dimensions. Hence, \(BA\) is not defined.

Key Concepts

Matrix Multiplication

Matrix multiplication is an essential operation where two matrices are multiplied together to produce a new matrix. This operation is not as simple as multiplying corresponding elements. Instead, it involves a row-by-column rule, where you take a row from the first matrix and a column from the second matrix to calculate each element of the product matrix.

For the multiplication to be defined, the number of columns in the first matrix must equal the number of rows in the second matrix. For example, if matrix \(A\) is a \(2 \times 2\) matrix and matrix \(B\) is a \(2 \times 3\) matrix, the product \(AB\) is possible and it results in a \(2 \times 3\) matrix.

Here's how it works step-by-step:

• Take each row from the first matrix.
• Multiply it by each column of the second matrix.
• Add up the results to get each element of the new matrix.

Therefore, having this understanding makes it clear why some matrix products are defined while others are not.

Matrix Subtraction

Matrix subtraction involves subtracting the elements of one matrix from the corresponding elements of another matrix. For two matrices to be subtracted, they must be of the same dimensions, meaning both must have the same number of rows and columns.

The operation is quite straightforward—subtract each element of the second matrix from the corresponding element in the first matrix.

• Ensure both matrices have identical dimensions.
• Subtract corresponding elements: if matrix \(A = \begin{bmatrix} a_{1} & a_{2} \ a_{3} & a_{4} \end{bmatrix}\) and matrix \(B = \begin{bmatrix} b_{1} & b_{2} \ b_{3} & b_{4} \end{bmatrix}\), then \(A - B = \begin{bmatrix} a_{1} - b_{1} & a_{2} - b_{2} \ a_{3} - b_{3} & a_{4} - b_{4} \end{bmatrix}\).

However, subtraction isn't defined when matrices have different shapes, like in the case where one matrix is \(2 \times 2\) and another is \(2 \times 3\).

Scalar Multiplication

Scalar multiplication involves multiplying every element of a matrix by a single number, known as a scalar. This is a very straightforward operation and is often used in conjunction with other matrix operations.

Here's the simple process for scalar multiplication:

• Take the scalar, which is just a number, say \(-1\) or \(3\).
• Multiply this scalar by each element in the matrix. If matrix \(A\) is \(\begin{bmatrix} a & b \ c & d \end{bmatrix}\) and the scalar is 2, then the result is \(\begin{bmatrix} 2a & 2b \ 2c & 2d \end{bmatrix}\).

This operation doesn't change the dimensions of the matrix, but it does change each element in a consistent way, scaling it by the same amount everywhere.

Matrix Squaring

Matrix squaring is a special case of matrix multiplication where a matrix is multiplied by itself. It’s essential for the original matrix to be square (having the same number of rows and columns) for this operation.

Here's how to do it:

• Multiply the matrix by itself using the regular matrix multiplication process.
• If matrix \(A\) is \(\begin{bmatrix} -1 & 3 \ 5 & 2 \end{bmatrix}\), then \(A^2 = A \times A\).

Squaring involves a detailed calculation since every element of the resulting matrix comes from performing dot-products between the corresponding row and column elements of the original matrix. This provides a new matrix that is of the same size as the original matrix, but with values transformed by the multiplication.