Topics
Relations and Functions
Relations and Functions
Algebra
Inverse Trigonometric Functions
Matrices
- Concept of Matrices
- Types of Matrices
- Equality of Matrices
- Operations on Matrices> Addition and Subtraction of Matrices
- Operations on Matrices>Scalar Multiplication
- Operations on Matrices> Matrix Multiplication
- Transpose of a Matrix
- Symmetric and Skew Symmetric Matrices
- Invertible Matrices
- Overview of Matrices
Calculus
Determinants
Vectors and Three-dimensional Geometry
Continuity and Differentiability
- Continuous and Discontinuous Functions
- Algebra of Continuous Functions
- Concept of Differentiability
- Derivatives of Composite Functions
- Derivative of Implicit Functions
- Derivative of Inverse Function
- Exponential and Logarithmic Functions
- Logarithmic Differentiation
- Derivatives of Functions in Parametric Forms
- Second Order Derivative
- Overview of Continuity and Differentiability
Linear Programming
Probability
Applications of Derivatives
Integrals
- Introduction of Integrals
- Integration as an Inverse Process of Differentiation
- Properties of Indefinite Integral
- Methods of Integration> Integration by Substitution
- Methods of Integration>Integration Using Trigonometric Identities
- Methods of Integration> Integration Using Partial Fraction
- Methods of Integration> Integration by Parts
- Integrals of Some Particular Functions
- Definite Integrals
- Fundamental Theorem of Integral Calculus
- Evaluation of Definite Integrals by Substitution
- Properties of Definite Integrals
- Overview of Integrals
Sets
Applications of the Integrals
Differential Equations
- Basic Concepts of Differential Equations
- Order and Degree of a Differential Equation
- General and Particular Solutions of a Differential Equation
- Methods of Solving Differential Equations> Variable Separable Differential Equations
- Methods of Solving Differential Equations> Homogeneous Differential Equations
- Methods of Solving Differential Equations>Linear Differential Equations
- Overview of Differential Equations
Vectors
- Basic Concepts of Vector Algebra
- Direction Ratios, Direction Cosine & Direction Angles
- Types of Vectors in Algebra
- Algebra of Vector Addition
- Multiplication in Vector Algebra
- Components of Vector in Algebra
- Vector Joining Two Points in Algebra
- Section Formula in Vector Algebra
- Product of Two Vectors
- Overview of Vectors
Three - Dimensional Geometry
Linear Programming
Probability
Introduction
In matrix algebra, the transpose of a matrix is one of the most basic and frequently used operations.
It is widely used in coordinate geometry, systems of equations, transformations, and data representation in higher mathematics and science.
Definition: Transpose of a Matrix
The transpose of a matrix is obtained by interchanging its rows and columns.
-
If a matrix is A, its transpose is denoted by AT
-
If A is of order m × n, then
AT is of order n × m - First row of A becomes first column of AT, and so on.
Properties
-
Transpose of Transpose
\[(A')' = A \quad \text{or} \quad (A^T)^T = A\]
Taking transpose twice gives back the original matrix. -
Scalar Multiplication
\[(kA)' = kA' \quad \text{or} \quad (kA)^T = kA^T\]
Scalar can be taken out unchanged. -
Transpose of Sum
\[(A + B)' = A' + B' \quad \text{or} \quad (A + B)^T = A^T + B^T\]
Transpose distributes over addition. -
Transpose of Product (Very Important)
\[(AB)' = B'A' \quad \text{or} \quad (AB)^T = B^T A^T\]
Order reverses in product.
Example 1
If \[\mathrm{A=}{ \begin{bmatrix} {-2} \\ {4} \\ {5} \end{bmatrix}},\mathrm{B=}{ \begin{bmatrix} {1} & {3} & {-6} \end{bmatrix}},\] verify that (AB)′ = B′A′.
Solution: We have
\[\mathrm{A}= \begin{bmatrix} -2 \\ 4 \\ 5 \end{bmatrix},\mathrm{B}= \begin{bmatrix} 1 & 3 & -6 \end{bmatrix}\]
then \[\mathrm{AB}= \begin{bmatrix} -2 \\ 4 \\ 5 \end{bmatrix} \begin{bmatrix} 1 & 3 & -6 \end{bmatrix}= \begin{bmatrix} -2 & -6 & 12 \\ 4 & 12 & -24 \\ 5 & 15 & -30 \end{bmatrix}\]
Now \[\mathrm{A}^{\prime}= \begin{bmatrix} -2 & 4 & 5 \end{bmatrix},\] \[\mathbf{B}^{\prime}= \begin{bmatrix} 1 \\ 3 \\ -6 \end{bmatrix}\]
\[\mathrm{B^{\prime}A^{\prime}}= \begin{bmatrix} 1 \\ 3 \\ -6 \end{bmatrix} \begin{bmatrix} -2 & 4 & 5 \end{bmatrix}= \begin{bmatrix} -2 & 4 & 5 \\ -6 & 12 & 15 \\ 12 & -24 & -30 \end{bmatrix}=(\mathrm{AB})^{\prime}\]
Clearly (AB)′ = B′A′
Real-Life Example
-
Think of a spreadsheet (like an Excel sheet or Google Sheet) with students as rows and subjects as columns.
-
Taking the transpose of that matrix is like rotating the table so that students become columns and subjects become rows.
Key Points: Transpose of a Matrix
-
Transpose = interchange rows and columns.
-
If A is \[m \times n\], then A' is \[n \times m\].
-
Standard notation: A' or \[A^T\].
-
Key properties: (A')' = A, (kA)' = kA', (A + B)' = A' + B', (AB)' = B'A'.
