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Chapter 6: Problem 1

State the dimension of each matrix. (a) \(\left[\begin{array}{l}1 \\ 2 \\ 3\end{array}\right]\) (b) \(\left[\begin{array}{lll}a & b & c \\ d & e & b\end{array}\right]\) (c) \(\left[\begin{array}{rr}3 & 0 \\ 1 & -4\end{array}\right]\)

Short Answer

Expert verified
(a) 3x1; (b) 2x3; (c) 2x2.

Step by step solution

01

Analyze Matrix (a)

Matrix (a) is a column vector. It has 3 rows and 1 column. Therefore, the dimension of matrix (a) is 3x1.
02

Analyze Matrix (b)

Matrix (b) is a 2-dimensional matrix with 2 rows and 3 columns. Thus, the dimension of matrix (b) is 2x3.
03

Analyze Matrix (c)

Matrix (c) is a 2-dimensional square matrix with 2 rows and 2 columns. Hence, the dimension of matrix (c) is 2x2.

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Key Concepts

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

Column Vector
A column vector is a specific type of matrix that consists of a single column and multiple rows. It is often used in mathematics and physics to represent coordinate vectors, gradients, or other one-dimensional data sets. In our exercise, matrix (a) is an example of a column vector.
In its simplest form, a column vector can be visualized as a list of numbers stacked vertically. Here are some characteristics of a column vector:
  • It has exactly one column.
  • The number of rows can vary and is denoted as "m", resulting in an "m x 1" dimension.
  • Commonly used in linear algebra for transformations and operations like matrix multiplication.
Understanding column vectors is essential when delving into more complex matrix operations and linear transformations.
Square Matrix
A square matrix is one where the number of rows is equal to the number of columns. This type of matrix plays a vital role in various mathematical computations, including solving linear equations, finding eigenvalues, and more. In our exercise, matrix (c) is an example of a square matrix with dimensions 2x2.
Square matrices have unique properties that are crucial in mathematical analysis:
  • They can have determinants, an important value used in many areas of physics and engineering.
  • Square matrices can be symmetric, diagonal, or identity matrices, each having specific characteristics and uses.
  • They are often used in solving systems of linear equations through methods such as Gaussian elimination or matrix inversion.
Knowing about square matrices and their properties can greatly enhance your mathematical toolkit.
2D Matrix
A 2D matrix, or two-dimensional matrix, is simply a grid of numbers arranged in rows and columns. This type of matrix is very common and is used to represent various forms of data in applied mathematics, computer science, and engineering. Both matrices (b) and (c) in our exercise are 2D matrices.
Key features of a 2D matrix:
  • Defined by its dimensions, "m x n", where "m" is the number of rows and "n" is the number of columns.
  • Can represent a variety of entities like images in computer graphics, transformation matrices in 3D modeling, or systems of equations in linear algebra.
  • Allows for operations like addition, subtraction, and multiplication, which are fundamental in matrix algebra.
Understanding 2D matrices is foundational for further studies in fields involving data representation and operations.

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Most popular questions from this chapter

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