/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 37 $$\text {Let } A=\left[\begin{ar... [FREE SOLUTION] | 91Ó°ÊÓ

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$$\text {Let } A=\left[\begin{array}{rr} -2 & 4 \\ 0 & 3 \end{array}\right] \text { and } B=\left[\begin{array}{rr} -6 & 2 \\ 4 & 0 \end{array}\right] . \text { Find each of the following.}$$ $$A B$$

Short Answer

Expert verified
The product matrix AB is \( \begin{pmatrix} 28 & -4 \ 12 & 0 \ \end{pmatrix} \)

Step by step solution

01

Write down the matrices

The matrices given in the exercise are: \[ A = \begin{pmatrix} -2 & 4 \ 0 & 3 \ \end{pmatrix} \text{ and } B = \begin{pmatrix} -6 & 2 \ 4 & 0 \ \end{pmatrix}. \]
02

Determine the elements of the product matrix AB

The product of matrices \(A\) and \(B\) is computed using the formula for matrix multiplication. For matrices \(A\) and \(B\), the element in row \(i\) and column \(j\) of the product matrix \(AB\) is given by: \[ (AB)_{ij} = \sum_{k=1}^{n} a_{ik} b_{kj} \]
03

Compute the element in the first row and first column

Calculate the element in the first row and first column: \[ (AB)_{11} = (-2)(-6) + (4)(4) = 12 + 16 = 28 \]
04

Compute the element in the first row and second column

Calculate the element in the first row and second column: \[ (AB)_{12} = (-2)(2) + (4)(0) = -4 + 0 = -4 \]
05

Compute the element in the second row and first column

Calculate the element in the second row and first column: \[ (AB)_{21} = (0)(-6) + (3)(4) = 0 + 12 = 12 \]
06

Compute the element in the second row and second column

Calculate the element in the second row and second column: \[ (AB)_{22} = (0)(2) + (3)(0) = 0 + 0 = 0 \]
07

Write the final product matrix

Putting all the elements together, the product matrix \(AB\) is: \[ AB = \begin{pmatrix} 28 & -4 \ 12 & 0 \ \end{pmatrix} \]

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

product of matrices
The product of matrices is calculated when two matrices are multiplied together. For this process to be valid, the number of columns in the first matrix must equal the number of rows in the second matrix. If matrix A is of size m×n and matrix B is of size n×p, the resulting matrix AB will be of size m×p. This means each element of the resulting matrix is formed by multiplying elements from corresponding rows and columns.

The computation requires a clear understanding of aligning the rows of the first matrix with the columns of the second matrix. Each element in the product matrix is calculated using the sum of the products of corresponding elements.
element computation
Let's dive into the computation of elements in a product matrix. Each entry \(c_{ij}\) in the resulting matrix C = AB is calculated by taking the dot product of the ith row of matrix A and the jth column of matrix B. The formula for each element is:

\[c_{ij} = \sum_{k=1}^{n} a_{ik} b_{kj}\]

Here, A and B are the original matrices, and C is the resulting product matrix.

For example, given matrices:

\[A = \begin{pmatrix}-2 & 4 \0 & 3\end{pmatrix}\] and

\[B = \begin{pmatrix}-6 & 2 \4 & 0\end{pmatrix}\]

To compute the element in the first row and first column of AB, use:

\[ (AB)_{11} = (-2)(-6) + (4)(4) = 12 + 16 = 28\]

Following similar steps, elements for the product matrix can be calculated systematically.
matrix algebra
Matrix algebra is a powerful tool for handling and manipulating matrices. It includes operations such as addition, subtraction, and multiplication of matrices. Among these, matrix multiplication is one of the key operations that is widely used in various applications including solving systems of linear equations, transformations in graphics, and more.

Matrix multiplication is not commutative, meaning that AB≠BA in general. However, it is associative ((AB)C = A(BC)) and distributive over matrix addition (A(B+C)=AB+AC). Understanding these properties is essential for simplifying complex matrix expressions and solving matrix-based problems.

Knowing how to multiply matrices correctly enables deeper exploration into linear transformations, algorithm optimization, and more. Practicing these basic concepts will build a strong foundation for more advanced topics in linear algebra.

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Most popular questions from this chapter

Solve each system by using the inverse of the coefficient matrix. $$\begin{aligned} 3 x+4 y &=-3 \\ -5 x+8 y &=16 \end{aligned}$$

Solve each system by using the inverse of the coefficient matrix. $$\begin{array}{l} -x+y=1 \\ 2 x-y=1 \end{array}$$

Use Cramer's rule to solve each system of equations. If \(D=0,\) use another method to determine the solution set. $$\begin{array}{c} 12 x+8 y=3 \\ 1.5 x+y=0.9 \end{array}$$

Solve each problem. Several years ago, mathematical ecologists created a model to analyze population dynamics of the endangered northern spotted owl in the Pacific Northwest. The ecologists divided the female owl population into three categories: juvenile (up to \(1 \text { yr old }),\) subadult \((1\) to 2 yr old ) and adult (over 2 yr old). They concluded that the change in the makeup of the northern spotted owl population in successive years could be described by the following matrix equation. $$ \left[\begin{array}{c} j_{n+1} \\ s_{n+1} \\ a_{n+1} \end{array}\right]=\left[\begin{array}{rrr} 0 & 0 & 0.33 \\ 0.18 & 0 & 0 \\ 0 & 0.71 & 0.94 \end{array}\right]\left[\begin{array}{c} j_{n} \\ s_{n} \\ a_{n} \end{array}\right] $$ The numbers in the column matrices give the numbers of females in the three age groups after \(n\) years and \(n+1\) years. Multiplying the matrices yields the following. \(j_{n+1}=0.33 a_{n}\) Each year 33 juvenile females are born for each 100 adult females. \(s_{n+1}=0.18 j_{n}\) Each year 18\% of the juvenile females survive to become subadults. \(a_{n+1}=0.71 s_{n}+0.94 a_{n} \quad\) Each year \(71 \%\) of the subadults survive to become adults, and \(94 \%\) of the adults survive. (a) Suppose there are currently 3000 female northern spotted owls made up of 690 juveniles, 210 subadults, and 2100 adults. Use the matrix equation on the preceding page to determine the total number of female owls for each of the next 5 yr. (b) Using advanced techniques from linear algebra, we can show that in the long run, $$ \left[\begin{array}{c} j_{n+1} \\ s_{n+1} \\ a_{n+1} \end{array}\right] \approx 0.98359\left[\begin{array}{c} j_{n} \\ s_{n} \\ a_{n} \end{array}\right] $$ What can we conclude about the long-term fate of the northern spotted owl? (c) In the model, the main impediment to the survival of the northern spotted owl is the number 0.18 in the second row of the 3 \(\times 3\) matrix. This number is low for two reasons. The first year of life is precarious for most animals living in the wild. In addition, juvenile owls must eventually leave the nest and establish their own territory. If much of the forest near their original home has been cleared, then they are vulnerable to predators while searching for a new home. Suppose that, thanks to better forest management, the number 0.18 can be increased to \(0.3 .\) Rework part (a) under this new assumption.

$$ A=\left[\begin{array}{ll} a_{11} & a_{12} \\ a_{21} & a_{22} \end{array}\right], \quad B=\left[\begin{array}{ll} b_{11} & b_{12} \\ b_{21} & b_{22} \end{array}\right], \quad \text { and } \quad C=\left[\begin{array}{ll} c_{11} & c_{12} \\ c_{21} & c_{22} \end{array}\right] $$ where all the elements are real numbers. Use these matrices to show that each statement is true for \(2 \times 2\) matrices. \(A+B=B+A\) (commutative property)

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