Problem 14
Question
Find the transpose of $$ A=\left[\begin{array}{r} 2 \\ -3 \\ 5 \end{array}\right] $$
Step-by-Step Solution
Verified Answer
The transpose of the matrix is
\[ A^T = \begin{bmatrix} 2 & -3 & 5 \end{bmatrix} \].
1Step 1: Understanding Transpose
To find the transpose of a matrix, you switch its rows with columns. For a column vector, this means turning the column into a row.
2Step 2: Write Down the Original Matrix
The original matrix A is given as: \[ A = \begin{bmatrix} 2 \ -3 \ 5 \end{bmatrix} \] This is a column vector with three elements.
3Step 3: Transpose the Matrix
To transpose the column vector into a row vector, we write:\[ A^T = \begin{bmatrix} 2 & -3 & 5 \end{bmatrix} \]Now, the vector has been changed from a column to a row.
Key Concepts
Column VectorRow VectorLinear Algebra
Column Vector
In linear algebra, a column vector is simply a collection of numbers arranged in a vertical list. This structure is crucial in many mathematical applications, as it allows for straightforward representation of data, such as coordinates in space or coefficients in equations.
Column vectors are often used to represent matrices with only one column, which can then be combined to form more complex matrices.
The notation for a column vector often looks like this:
This organization is especially useful in various fields, including physics, engineering, and computer science, where data organization crucially affects calculations and interpretations.
Column vectors are often used to represent matrices with only one column, which can then be combined to form more complex matrices.
The notation for a column vector often looks like this:
- The entries are enclosed in square or round brackets.
- The vector is aligned vertically.
This organization is especially useful in various fields, including physics, engineering, and computer science, where data organization crucially affects calculations and interpretations.
Row Vector
A row vector, in contrast to a column vector, is an array of numbers organized in a horizontal line. It reflects one-dimensional data representation, akin to a row in a table or spreadsheet.
Row vectors are pivotal in many computational tasks, particularly in data manipulation and linear transformations within mathematics and related disciplines.
To identify a row vector, you can recognize it through these characteristics:
Transpose is essentially the process of swapping the order from vertical to horizontal or vice versa, which is a common operation in manipulating matrices for various applications, like solving systems of equations or transforming geometric data.
Row vectors are pivotal in many computational tasks, particularly in data manipulation and linear transformations within mathematics and related disciplines.
To identify a row vector, you can recognize it through these characteristics:
- The elements are listed horizontally.
- They are enclosed within brackets, in a single row.
Transpose is essentially the process of swapping the order from vertical to horizontal or vice versa, which is a common operation in manipulating matrices for various applications, like solving systems of equations or transforming geometric data.
Linear Algebra
Linear Algebra is a branch of mathematics focused on vectors, vector spaces, and linear transformations. It's the foundation for understanding complex systems and is pivotal to various fields such as physics, computer science, and engineering.
This discipline revolves around
For students delving into linear algebra, comprehending how elements like column and row vectors interact within a matrix framework is essential. These elements not only shape the structure of data but also facilitate the application of algorithms and theorems in solving real-world problems effectively.
This discipline revolves around
- Matrix operations and transformations
- Understanding vector spaces
- Solving systems of linear equations
For students delving into linear algebra, comprehending how elements like column and row vectors interact within a matrix framework is essential. These elements not only shape the structure of data but also facilitate the application of algorithms and theorems in solving real-world problems effectively.
Other exercises in this chapter
Problem 13
Reduce the system of linear equations to upper triangular form and solve. $$ \begin{array}{r} 3 x-y=1 \\ -3 x+y=4 \end{array} $$
View solution Problem 13
Suppose a vector \(\left[\begin{array}{l}x_{1} \\ x_{2}\end{array}\right]\) has length 3 and is \(15^{\circ}\) clockwise from the positive \(x_{1}\) -axis. Find
View solution Problem 14
Reduce the system of linear equations to upper triangular form and solve. $$ \begin{aligned} 2 x+3 y &=5 \\ -\quad y &=-2+\frac{2}{3} x \end{aligned} $$
View solution Problem 14
Normalize \([0,-3,1,3]^{\prime}\).
View solution