Transpose of a Matrix-Addition & Multiplication Property of Transpose, Solved Examples

Before learning how to find the transpose of a matrix, first let us learn, what a matrix is?

What is a Matrix?

A matrix is a rectangular array of numbers or functions arranged in a fixed number of rows and columns.

There are many types of matrices. Let us consider a matrix to understand more about them.

\(\begin{array}{l}A = \begin{bmatrix} 2 & 13\\ -9 & 11\\ 3 & 17 \end{bmatrix}_{3 \times 2}\end{array} \)

The above matrix A is of order 3 × 2. Thus, there are a total of 6 elements.

The horizontal array is known as rows and the vertical array is known as Columns.

Now, let us take another matrix.

\(\begin{array}{l}B = \begin{bmatrix} 2 & -9 & 3\\ 13 & 11 & 17 \end{bmatrix}_{2 \times 3}\end{array} \)

The number of rows in matrix A is greater than the number of columns, such a matrix is called a Vertical matrix.

The number of columns in matrix B is greater than the number of rows. Such a matrix is called a Horizontal matrix.

One thing to notice here, if elements of A and B are listed, they are the same in number and each element that is there in A is there in B too. So, is A = B?

Before answering this, we should know how to decide the equality of the matrices.

A matrix P is said to be equal to matrix Q if their orders are the same and each corresponding element of P is equal to that of Q.

That is, if

\(\begin{array}{l}P= [p_{ij}]_{m\times n} \ and\ Q =[q_{ij}]_{r\times s}\end{array} \)

are two matrices such that P = Q, then:

Transpose of a Matrix Definition

The transpose of a matrix is found by interchanging its rows into columns or columns into rows. The transpose of the matrix is denoted by using the letter “T” in the superscript of the given matrix. For example, if “A” is the given matrix, then the transpose of the matrix is represented by A’ or AT.

The following statement generalizes the matrix transpose:

\(\begin{array}{l}If\ A = [a_{ij}]_{m×n}, then\ A’ =[a_{ij}]_{n×m}.\end{array} \)

Thus Transpose of a Matrix is defined as “A Matrix which is formed by turning all the rows of a given matrix into columns and vice-versa.”

How to Find the Transpose of a Matrix?

Consider an example, if a matrix is a 2×3 matrix. It means it has 2 rows and 3 columns. While finding the transpose of a matrix, the elements in the first row of the given matrix are written in the first column of the new matrix. Similarly, the elements in the second row of the given matrix are written in the second column of the new matrix. Hence, the order of the new matrix becomes 3×2, as it has 3 rows and 2 columns.

Transpose of a Matrix
Let’s Work Out- Example- Find the transpose of the given matrix   \(\begin{array}{l}M = \begin{bmatrix} 2 & -9 & 3 \\ 13 & 11 & -17 \\ 3 & 6 & 15 \\ 4 & 13 & 1 \end{bmatrix} \end{array} \)   Solution- Given a matrix of the order 4×3. The transpose of a matrix is given by interchanging rows and columns.   \(\begin{array}{l}M^T = \begin{bmatrix} 2 & 13 & 3 & 4 \\ -9 & 11 & 6 & 13\\ 3 & -17 & 15 & 1 \end{bmatrix}\end{array} \)  

Properties of Transpose of a Matrix

To understand the properties of the matrix transpose, we will take two matrices A and B which have equal order. Some properties of the transpose of a matrix are given below:

(i) Transpose of the Transpose Matrix

If we take the transpose of the transpose matrix, the matrix obtained is equal to the original matrix. Hence, for a matrix A, (A’)’ = A 

What basically happens, is that any element of A, i.e. aij gets converted to aji if the transpose of A is taken. So, taking transpose again, it gets converted to aij, which was the original matrix A.

Example: If \(\begin{array}{l}N = \begin{bmatrix} 22 & -21 & -99 \\ 85 & 31 & -2\sqrt{3} \\ 7 & -12 & 57 \end{bmatrix},\end{array} \)   Then \(\begin{array}{l}N’ = \begin{bmatrix} 22 &85 & 7 \\ -21 & 31 & -12 \\ -99 & -2\sqrt{3} & 57 \end{bmatrix}\end{array} \)   Now, \(\begin{array}{l}(N’)’ =  \begin{bmatrix} 22 & -21 & -99 \\ 85 & 31 & -2\sqrt{3} \\ 7 & -12 & 57 \end{bmatrix} \end{array} \)   \(\begin{array}{l} = N\end{array} \)  

(ii) Addition Property of Transpose

Transpose of an addition of two matrices A and B obtained will be exactly equal to the sum of the transpose of individual matrices A and B.

This means,

\(\begin{array}{l}(A+B)’ = A’+B’\end{array} \)

Example- \(\begin{array}{l}If\ P= \begin{bmatrix} 2 & -3 & 8 \\ 21 & 6 & -6  \\ 4 & -33 & 19 \end{bmatrix} \ and\ Q = \begin{bmatrix} 1 & -29 & -8 \\ 2 & 0 & 3 \\ 17 & 15 & 4 \end{bmatrix} \end{array} \) \(\begin{array}{l}P + Q = \begin{bmatrix} 2+1 & -3-29 & 8-8 \\ 21+2 & 6+0 & -6+3  \\ 4+17 & -33+15 & 19+4 \end{bmatrix} = \begin{bmatrix} 3 & -32 & 0 \\ 23 & 6 & -3  \\ 21 & -18 & 23 \end{bmatrix} \end{array} \) \(\begin{array}{l}(P+Q)’ = \begin{bmatrix} 3 & 23 & 21 \\ -32 & 6 & -18  \\ 0 & -3 & 23 \end{bmatrix} \end{array} \) \(\begin{array}{l}P’+Q’ = \begin{bmatrix} 2 & 21 & 4 \\ -3 & 6 & -33  \\ 8 & -6 & 19 \end{bmatrix} +  \begin{bmatrix} 1 & 2 & 17 \\ -29 & 0 & 15  \\ -8 & 3 & 4 \end{bmatrix} = \begin{bmatrix} 3 & 23 & 21 \\ -32 & 6 & -18  \\ 0 & -3 & 23 \end{bmatrix} \end{array} \)   \(\begin{array}{l} = (P+Q)’\end{array} \)   So, we can observe that \(\begin{array}{l}(P+Q)’= P’+Q’.\end{array} \)

(iii) Multiplication by Constant

If a matrix is multiplied by a constant and its transpose is taken, then the matrix obtained is equal to the transpose of the original matrix multiplied by that constant. That is,

\(\begin{array}{l}(kA)’ = kA’\end{array} \)

where k is a constant

Example- \(\begin{array}{l}If\ P = \begin{bmatrix} 2 & 8 & 9 \\ 11 & -15 & -13  \end{bmatrix}_{2×3}  and\ k\ is\ a\ constant,\ then\ (kP)’\end{array} \) \(\begin{array}{l}= \begin{bmatrix} 2k & 11k \\ 8k & -15k \\ 9k &-13k \end{bmatrix}_{2×3} \end{array} \) \(\begin{array}{l}kP’= k \begin{bmatrix} 2 & 11 \\ 8 & -15 \\ 9 & -13  \end{bmatrix}_{2×3} = \begin{bmatrix} 2k & 11k \\ 8k & -15k \\ 9k &-13k \end{bmatrix}_{2×3} = (kP)’\end{array} \) We can observe that \(\begin{array}{l}(kP)’ = kP’.\end{array} \)

(iv) Multiplication Property of Transpose

Transpose of the product of two matrices is equal to the product of transpose of the two matrices in reverse order. That is

\(\begin{array}{l}(AB)’ = B’A’\end{array} \)

Example: \(\begin{array}{l}A = \begin{bmatrix} 9 & 8 \\ 2 & -3 \end{bmatrix} and\ B = \begin{bmatrix} 4 & 2 \\ 1 & 0 \end{bmatrix} \end{array} \) Let us find A×B. \(\begin{array}{l}A\times B = \begin{bmatrix} 44 & 18 \\ 5 & 4 \end{bmatrix} \Rightarrow (AB)’ = \begin{bmatrix} 44 & 5 \\ 18 & 4 \end{bmatrix} \end{array} \) \(\begin{array}{l}B’A’ = \begin{bmatrix} 4 & 1 \\ 2 & 0 \end{bmatrix} \begin{bmatrix} 9 & 2 \\ 8 & -3 \end{bmatrix}\end{array} \) \(\begin{array}{l}= \begin{bmatrix} 44 & 5 \\ 18 & 4 \end{bmatrix} = (AB)’\end{array} \) \(\begin{array}{l}\therefore (AB)’ = B’A’\end{array} \) \(\begin{array}{l}A’B’ =\begin{bmatrix} 9 & 2 \\ 8 & -3 \end{bmatrix} \begin{bmatrix} 4 & 1 \\ 2 & 0 \end{bmatrix} = \begin{bmatrix} 40 & 9 \\ 26 & 8 \end{bmatrix}\end{array} \) We can clearly observe from here that (AB)’≠A’B’.

Those were properties of matrix transpose which are used to prove several theorems related to matrices.

Transpose of a Matrix Examples

Go through the following problems to understand how to find the transpose of a matrix.

Example 1:

If matrix

\(\begin{array}{l}A = \begin{bmatrix} 1 & 2 & 3\\ 4 & 5 & 6 \end{bmatrix}.\end{array} \)

Find the transpose of matrix A.

Solution:

Given:

Matrix

\(\begin{array}{l}A = \begin{bmatrix} 1 & 2 & 3\\ 4 & 5 & 6 \end{bmatrix}\end{array} \)

On interchanging the rows and columns of the given matrix, the transpose of matrix A is given as:

\(\begin{array}{l}A^{T} = \begin{bmatrix} 1 & 4\\ 2 & 5\\ 3 & 6 \end{bmatrix}\end{array} \)

Therefore, the transpose of matrix A,

\(\begin{array}{l}A^{T} = \begin{bmatrix} 1 & 4\\ 2 & 5\\ 3 & 6 \end{bmatrix}\end{array} \)

Example 2:

Find the transpose for the given 2×2 matrix,

\(\begin{array}{l}X =\begin{bmatrix} 7 & 11 \\ 21 & 16 \end{bmatrix}\end{array} \)

Solution:

Given 2×2 matrix,

\(\begin{array}{l}X =\begin{bmatrix} 7 & 11 \\ 21 & 16 \end{bmatrix}\end{array} \)

Hence, the transpose of the given 2×2 matrix is:

\(\begin{array}{l}X^{T} =\begin{bmatrix} 7 & 21 \\ 11 & 16 \end{bmatrix}\end{array} \)

Practice Problems

  1. Give matrix \(\begin{array}{l}A=\begin{bmatrix}1 & 2 & 2\\2 & 1 & -2\\4 & -3 & 1\end{bmatrix}.\end{array} \) Find the transpose of A and then prove that (AT)T = A.
  2. Verify the addition property for the transpose of matrices \(\begin{array}{l}P=\begin{bmatrix}4 & 0 & 3\\5 & -1 & -2\\1 & 2 & 1\end{bmatrix}\textrm{and}\ Q=\begin{bmatrix}5 & 1 & 1\\3 & -4 & 0\\2 & 1 & -3\end{bmatrix}\end{array} \)  
  3. Find AT for the matrix \(\begin{array}{l}A=\begin{bmatrix}1 & -4 & 9\\5 & 3 & -2\end{bmatrix}\end{array} \)  

Frequently Asked Questions

Q1

What is the transpose of a matrix?

The transpose of a matrix can be defined as an operator which can switch the rows and column indices of a matrix i.e. it flips a matrix over its diagonal.

Q2

How to calculate the transpose of a Matrix?

To calculate the transpose of a matrix, simply interchange the rows and columns of the matrix i.e. write the elements of the rows as columns and write the elements of a column as rows.

Q3

What is the Addition Property of Transpose?

The addition property of transpose is that the sum of two transpose matrices will be equal to the sum of the transpose of individual matrices. So,

Q4

What is the Multiplication Property of Transpose?

The multiplication property of transpose is that the transpose of a product of two matrices will be equal to the product of the transpose of individual matrices in reverse order. So,

  • (A×B)′ = B′ × A′

Er. Neeraj K.Anand is a freelance mentor and writer who specializes in Engineering & Science subjects. Neeraj Anand received a B.Tech degree in Electronics and Communication Engineering from N.I.T Warangal & M.Tech Post Graduation from IETE, New Delhi. He has over 30 years of teaching experience and serves as the Head of Department of ANAND CLASSES. He concentrated all his energy and experiences in academics and subsequently grew up as one of the best mentors in the country for students aspiring for success in competitive examinations. In parallel, he started a Technical Publication "ANAND TECHNICAL PUBLISHERS" in 2002 and Educational Newspaper "NATIONAL EDUCATION NEWS" in 2014 at Jalandhar. Now he is a Director of leading publication "ANAND TECHNICAL PUBLISHERS", "ANAND CLASSES" and "NATIONAL EDUCATION NEWS". He has published more than hundred books in the field of Physics, Mathematics, Computers and Information Technology. Besides this he has written many books to help students prepare for IIT-JEE and AIPMT entrance exams. He is an executive member of the IEEE (Institute of Electrical & Electronics Engineers. USA) and honorary member of many Indian scientific societies such as Institution of Electronics & Telecommunication Engineers, Aeronautical Society of India, Bioinformatics Institute of India, Institution of Engineers. He has got award from American Biographical Institute Board of International Research in the year 2005.

CBSE Class 12 Maths Syllabus 2025-26 with Marks Distribution

The table below shows the marks weightage along with the number of periods required for teaching. The Maths theory paper is of 80 marks, and the internal assessment is of 20 marks which totally comes out to be 100 marks.

CBSE Class 12 Maths Syllabus And Marks Distribution 2023-24

Max Marks: 80

No.UnitsMarks
I.Relations and Functions08
II.Algebra10
III.Calculus35
IV.Vectors and Three – Dimensional Geometry14
V.Linear Programming05
VI.Probability08
Total Theory80
Internal Assessment20
Grand Total100

Unit-I: Relations and Functions

1. Relations and Functions

Types of relations: reflexive, symmetric, transitive and equivalence relations. One to one and onto functions.

2. Inverse Trigonometric Functions

Definition, range, domain, principal value branch. Graphs of inverse trigonometric functions.

Unit-II: Algebra

1. Matrices

Concept, notation, order, equality, types of matrices, zero and identity matrix, transpose of a matrix, symmetric and skew symmetric matrices. Operations on matrices: Addition and multiplication and multiplication with a scalar. Simple properties of addition, multiplication and scalar multiplication. Noncommutativity of multiplication of matrices and existence of non-zero matrices whose product is the zero matrix (restrict to square matrices of order 2). Invertible matrices and proof of the uniqueness of inverse, if it exists; (Here all matrices will have real entries).

2. Determinants

Determinant of a square matrix (up to 3 x 3 matrices), minors, co-factors and applications of determinants in finding the area of a triangle. Adjoint and inverse of a square matrix. Consistency, inconsistency and number of solutions of system of linear equations by examples, solving system of linear equations in two or three variables (having unique solution) using inverse of a matrix.

Unit-III: Calculus

1. Continuity and Differentiability

Continuity and differentiability, derivative of composite functions, chain rule, derivative of inverse trigonometric functions like sin-1 x, cos-1 x and tan-1 x, derivative of implicit functions. Concept of exponential and logarithmic functions.
Derivatives of logarithmic and exponential functions. Logarithmic differentiation, derivative of functions expressed in parametric forms. Second order derivatives.

2. Applications of Derivatives

Applications of derivatives: rate of change of quantities, increasing/decreasing functions, maxima and minima (first derivative test motivated geometrically and second derivative test given as a provable tool). Simple problems (that illustrate basic principles and understanding of the subject as well as real-life situations).

3. Integrals 

Integration as inverse process of differentiation. Integration of a variety of functions by substitution, by partial fractions and by parts, Evaluation of simple integrals of the following types and problems based on them.

Fundamental Theorem of Calculus (without proof). Basic properties of definite integrals and evaluation of definite integrals.

4. Applications of the Integrals

Applications in finding the area under simple curves, especially lines, circles/ parabolas/ellipses (in standard form only)

5. Differential Equations

Definition, order and degree, general and particular solutions of a differential equation. Solution of differential equations by method of separation of variables, solutions of homogeneous differential equations of first order and first degree. Solutions of linear differential equation of the type:

dy/dx + py = q, where p and q are functions of x or constants.

dx/dy + px = q, where p and q are functions of y or constants.

Unit-IV: Vectors and Three-Dimensional Geometry

1. Vectors

Vectors and scalars, magnitude and direction of a vector. Direction cosines and direction ratios of a vector. Types of vectors (equal, unit, zero, parallel and collinear vectors), position vector of a point, negative of a vector, components of a vector, addition of vectors, multiplication of a vector by a scalar, position vector of a point dividing a line segment in a given ratio. Definition, Geometrical Interpretation, properties and application of scalar (dot) product of vectors, vector (cross) product of vectors.

2. Three – dimensional Geometry

Direction cosines and direction ratios of a line joining two points. Cartesian equation and vector equation of a line, skew lines, shortest distance between two lines. Angle between two lines.

Unit-V: Linear Programming

1. Linear Programming

Introduction, related terminology such as constraints, objective function, optimization, graphical method of solution for problems in two variables, feasible and infeasible regions (bounded or unbounded), feasible and infeasible solutions, optimal feasible solutions (up to three non-trivial constraints).

Unit-VI: Probability

1. Probability

Conditional probability, multiplication theorem on probability, independent events, total probability, Bayes’ theorem, Random variable and its probability distribution, mean of random variable.

Students can go through the CBSE Class 12 Syllabus to get the detailed syllabus of all subjects. Get access to interactive lessons and videos related to Maths and Science with ANAND CLASSES’S App/ Tablet.

Frequently Asked Questions on CBSE Class 12 Maths Syllabus 2025-26

Q1

Is Calculus an important chapter in the CBSE Class 12 Maths Syllabus?

Yes, Calculus is an important chapter in the CBSE Class 12 Maths Syllabus. It is for 35 marks which means that if a student is thorough with this chapter will be able to pass the final exam.

Q2

How many units are discussed in the CBSE Class 12 Maths Syllabus?

In the CBSE Class 12 Maths Syllabus, about 6 units are discussed, which contains a total of 13 chapters.

Q3

How many marks are allotted for internals in the CBSE Class 12 Maths syllabus?

About 20 marks are allotted for internals in the CBSE Class 12 Maths Syllabus. Students can score it with ease through constant practice.