/*! 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 47 Suppose that matrix \(A\) has di... [FREE SOLUTION] | 91Ó°ÊÓ

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Suppose that matrix \(A\) has dimension \(2 \times 3, B\) has dimension \(3 \times 5,\) and \(C\) has dimension \(5 \times 2 .\) Decide whether the given product can be calculated. If it can, determine its dimension. $$B A$$

Short Answer

Expert verified
The product BA cannot be calculated because the inner dimensions do not match.

Step by step solution

01

- Understand the dimensions of the matrices

Matrix A has dimensions 2x3, matrix B has dimensions 3x5, and matrix C has dimensions 5x2. To determine if we can multiply two matrices, we need to check the inner dimensions.
02

- Determine if BA can be calculated

For matrix multiplication, the number of columns in the first matrix must equal the number of rows in the second matrix. In this case, for BA to be calculated, the number of columns in B (5) must equal the number of rows in A (2). Since they are not equal, the product BA cannot be calculated.

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Key Concepts

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

matrix dimensions
Matrix dimensions are crucial in determining whether two matrices can be multiplied. Every matrix is defined by its size or dimensions, expressed as rows by columns, such as a 2x3 matrix. Here, '2x3' means the matrix has 2 rows and 3 columns. Understanding this notation makes it easier to visualize and work with matrices.

When looking at the dimensions of matrices, we must pay close attention to how they align for multiplication. For instance, in our example, Matrix A is 2x3, Matrix B is 3x5, and Matrix C is 5x2.

Before attempting to multiply any matrices, always double-check their dimensions to ensure the operation is possible. This understanding of dimensions forms the foundation of matrix multiplication.
multiplication rules
Matrix multiplication isn't just about multiplying individual elements; there are specific rules to follow. To multiply two matrices, the number of columns in the first matrix must match the number of rows in the second matrix. This requirement is known as conforming matrices.

For instance, matrix A (2x3) and matrix B (3x5) can be multiplied because the number of columns in A (3) matches the number of rows in B (3). However, matrix B (3x5) and matrix A (2x3) cannot be multiplied in that order, as the number of columns in B (5) does not match the number of rows in A (2). This is exactly what we found in our exercise example with BA.

Once you ensure that the matrices conform, the result of the multiplication will have dimensions equal to the outer dimensions of the two matrices being multiplied. If A (2x3) is multiplied by B (3x5), the resulting matrix will be 2x5, meaning it will have 2 rows and 5 columns.
linear algebra
Linear Algebra is a branch of mathematics focusing on vectors, vector spaces (or linear spaces), and linear transformations. Matrices are fundamental in linear algebra as they represent linear transformations and encode systems of linear equations.

Understanding matrix multiplication is crucial in linear algebra as it allows for operations such as transforming vectors, solving systems of equations, and more. These multiplications reveal how one set of values influences another set through the transformation encoded by the matrix.

For example, multiplying a matrix by a vector can transform the vector in ways like rotating, scaling, or translating it in space. Mastery of linear algebra, including the accurate application of matrix multiplication rules and understanding matrix dimensions, opens up a wide range of applications in science, engineering, computer graphics, machine learning, and more.

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Most popular questions from this chapter

Find the equation of the parabola \(y=a x^{2}+b x+c\) that passes through the points \((2,3),(-1,0),\) and \((-2,2)\) Find the equation of the parabola \(y=a x^{2}+b x+c\) that passes through the points \((-2,4),(2,2),\) and \((4,9)\)

Use Cramer's rule to solve each system of equations. If \(D=0,\) use another method to determine the solution set. $$\begin{aligned} &4 x+3 y=-7\\\ &2 x+3 y=-11 \end{aligned}$$

Use Cramer's rule to solve each system of equations. If \(D=0,\) use another method to determine the solution set. $$\begin{array}{r} 2 x-y+4 z=-2 \\ 3 x+2 y-z=-3 \\ x+4 y+2 z=17 \end{array}$$

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.

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

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