Topics
Relations and Functions
Relations and Functions
Inverse Trigonometric Functions
- Basics of Inverse Trigonometric Functions
- Domain, Range & Principal Value
- Graphs of Inverse Trigonometric Functions
- Properties of Inverse Trigonometric Functions > Self-adjusting Property
- Overview of Inverse Trigonometric Functions
- Properties of Inverse Trigonometric Functions > Reciprocal Property
- Properties of Inverse Trigonometric Functions > Negative Argument Property
- Properties of Inverse Trigonometric Functions > Complementary Property
- Properties of Inverse Trigonometric Functions > Conversion Property
- Properties of Inverse Trigonometric Functions > Addition & Subtraction Formula for Inverse Tangent
- Properties of Inverse Trigonometric Functions > Double-angle Property
- Properties of Inverse Trigonometric Functions > Triple-angle Property
- Properties of Inverse Trigonometric Functions > Addition–Subtraction Formula for Inverse Sine & Cosine
Algebra
Calculus
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
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- Invertible Matrices
- Overview of Matrices
Vectors and Three-dimensional Geometry
Determinants
Continuity and Differentiability
- Continuous and Discontinuous Functions
- Algebra of Continuous Functions
- Concept of Differentiability
- Derivatives of Composite Functions
- Differentiation of Implicit Functions
- Derivative of Inverse Trigonometric Function
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- Logarithmic Differentiation
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Linear Programming
Applications of Derivatives
Probability
Integrals
- Integration
- Integration as an Inverse Process of Differentiation
- Properties of Indefinite Integral
- Methods of Integration> Integration by Substitution
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- Methods of Integration> Integration Using Partial Fraction
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- Integrals of Some Particular Functions
- Definite Integrals
- Fundamental Theorem of Integral Calculus
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- 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 in Vector
- Types of Vectors in Algebra
- Algebra of Vectors > Addition & Subtraction of Two Vectors
- Multiplication in Vector Algebra
- Components of Vector in Algebra
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- Product of Two Vectors > Scalar (Dot) Product
- Overview of Vectors
Three - Dimensional Geometry
Linear Programming
Probability
Introduction
Matrix multiplication is a fundamental operation in algebra that helps us represent and solve systems of equations, perform coordinate transformations, and model real-life situations like network flows and data transformations.
Definition: Matrix Multiplication
Let \[A = [a_{ij}]\] be an \[m \times n\] matrix and \[B = [b_{jk}]\] be an \[n \times p\] matrix.
Then the product C = AB is an \[m \times p\] matrix \[C = [c_{ik}]\], where each entry \[c_{ik}\] is given by:
Properties
| Property | Rule / Formula |
|---|---|
| Non-commutativity | In general, \[AB \neq BA\] |
| Associativity | \[(AB)C = A(BC)\] |
| Left distributive law | \[A(B + C) = AB + AC\] |
| Right distributive law | \[(A + B)C = AC + BC\] |
| Multiplication by zero matrix | AO = O and OA = O |
| Identity matrix property | AI = IA = A |
| Cancellation law | From AB = AC, we cannot always conclude B = C |
Example 1
If \[\mathrm{A=} \begin{bmatrix} 0 & 6 & 7 \\ -6 & 0 & 8 \\ 7 & -8 & 0 \end{bmatrix},\mathrm{B=} \begin{bmatrix} 0 & 1 & 1 \\ 1 & 0 & 2 \\ 1 & 2 & 0 \end{bmatrix},\mathrm{C=} \begin{bmatrix} 2 \\ -2 \\ 3 \end{bmatrix}\]
Calculate AC, BC and (A + B)C. Also, verify that (A + B)C = AC + BC
Solution: Now, \[\mathbf{A}+\mathbf{B}= \begin{bmatrix} 0 & 7 & 8 \\ -5 & 0 & 10 \\ 8 & -6 & 0 \end{bmatrix}\]
So \[\mathrm{(A+B)C}= \begin{bmatrix} 0 & 7 & 8 \\ -5 & 0 & 10 \\ 8 & -6 & 0 \end{bmatrix} \begin{bmatrix} 2 \\ -2 \\ 3 \end{bmatrix}= \begin{bmatrix} 0-14+24 \\ -10+0+30 \\ 16+12+0 \end{bmatrix}= \begin{bmatrix} 10 \\ 20 \\ 28 \end{bmatrix}\]
Further \[\mathrm{AC}= \begin{bmatrix} 0 & 6 & 7 \\ -6 & 0 & 8 \\ 7 & -8 & 0 \end{bmatrix} \begin{bmatrix} 2 \\ -2 \\ 3 \end{bmatrix}= \begin{bmatrix} 0-12+21 \\ -12+0+24 \\ 14+16+0 \end{bmatrix}= \begin{bmatrix} 9 \\ 12 \\ 30 \end{bmatrix}\]
and \[\mathrm{BC}= \begin{bmatrix} 0 & 1 & 1 \\ 1 & 0 & 2 \\ 1 & 2 & 0 \end{bmatrix} \begin{bmatrix} 2 \\ -2 \\ 3 \end{bmatrix}= \begin{bmatrix} 0-2+3 \\ 2+0+6 \\ 2-4+0 \end{bmatrix}= \begin{bmatrix} 1 \\ 8 \\ -2 \end{bmatrix}\]
So \[\mathrm{AC}+\mathrm{BC}= \begin{bmatrix} 9 \\ 12 \\ 30 \end{bmatrix}+ \begin{bmatrix} 1 \\ 8 \\ -2 \end{bmatrix}= \begin{bmatrix} 10 \\ 20 \\ 28 \end{bmatrix}\]
Clearly, (A + B) C = AC + BC
CISCE: Class 10
Key Points: Matrix Multiplication
-
Matrix multiplication is row-by-column, not term-wise.
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Product AB exists only if columns of A = rows of B.
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If A is \[m \times n\] and B is \[n \times p\], then AB is \[m \times p\].
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In general, \[AB \neq BA\], and sometimes one product may not even be defined.
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Matrix multiplication is associative and distributive over addition.
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Identity matrix acts as a multiplicative identity: AI = IA = A.
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Zero matrix absorbs multiplication: AO = OA = O.
Video Tutorials
Shaalaa.com | Matrices part 26 (Property matrices multiplication)
Related QuestionsVIEW ALL [45]
Answer the following question:
Two farmers Shantaram and Kantaram cultivate three crops rice,wheat and groundnut. The sale (In Rupees) of these crops by both the farmers for the month of April and may 2008 is given below,
| April sale (In Rs.) | |||
| Rice | Wheat | Groundnut | |
| Shantaram | 15000 | 13000 | 12000 |
| Kantaram | 18000 | 15000 | 8000 |
| May sale (In Rs.) | |||
| Rice | Wheat | Groundnut | |
| Shantaram | 18000 | 15000 | 12000 |
| Kantaram | 21000 | 16500 | 16000 |
Find the increase in sales from April to May for every crop of each farmer.
