September 11, 2024
Overview: Gain insight into CBSE Class 12 Applied Maths Algebra with our comprehensive guide. Learn about the syllabus, key topics, and essential preparation tips. Perfect for students aiming for clarity and success in their board exams.
Recognizing the need for practical mathematics in today's fast-paced commercial world, CBSE introduced a fresh elective course - Class 12 Applied Maths.
And when we delve into the core of this subject, Algebra stands tall as one of its quintessential components. With Algebra crowned as one of its pivotal topics, it's imperative for scholars to gain a clear grasp.
To give you a perspective, in the CBSE Class 12 Board Exam, Algebra isn't just another chapter; it claims a whopping 10 marks out of the total 80. Hence, a focused understanding of it isn't a choice but a necessity.
Here are the points to be discussed in the blog:
You will study various topics in the Applied Maths Algebra section: Matrices, Determinants, Cramer’s rule and its application, and Simple applications of matrices and determinants, including the Leontief input-output model for two variables.
Knowing the syllabus will help you know important Applied Maths Algebra CBSE class 12 topics and focus more on those topics to score good marks in the exam. The table below shows the CBSE class 12 Applied Maths Algebra syllabus 2025:
Topics | Explanation of Topics |
Matrices | Concept of matrices, Notation, order, equality, types of matrices, zero and identity matrix, transpose of a matrix, symmetric and skew-symmetric matrices. Operation on matrices: Addition and multiplication and multiplication with a scalar. Simple properties of addition, multiplication, and scalar multiplication. Non-commutativity of multiplication of matrices and existence of non-zero matrices whose product is the zero matrices (restricted to square matrices of order 2). Concept of elementary row and column operations. Invertible matrices and proof of the uniqueness of inverse, if it exists; (Here, all matrices will have real entries). |
Determinants | Concept of Determinant, Determinant of a square matrix (up to 3 × 3 matrices), properties of determinants, minors, cofactors, 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 a system of linear equations by examples, solving system of linear equations in two or three variables (having a unique solution) using an inverse of a matrix |
Cramer’s Rule and its Application | Concept of Cramer’s rule and its Application, Derivation of application. |
Simple applications of matrices and determinants, including Leontiff input-output model for two variables | Concept of Simple applications of matrices and determinants, including Leontiff input-output model for two variables. |
As per the CBSE Class 12 Applied Maths Syllabus, the main topics that you will be studying in Algebra are:
Here's a table with important definitions and concepts related to CBSE Class 12 Applied Mathematics Algebra:
Term/Concept | Definition |
---|---|
Algebra | A branch of mathematics that deals with symbols and the rules for manipulating those symbols. |
Polynomial | An algebraic expression consisting of variables, coefficients, and exponents combined using operations. |
Degree of a Polynomial | The highest exponent of the variable in a polynomial expression. |
Zero of a Polynomial | A value of the variable that makes the polynomial equal to zero. |
Factorization | Expressing a polynomial as a product of two or more polynomials. |
Factor Theorem | If (x - a) is a factor of a polynomial P(x), then P(a) = 0. |
Remainder Theorem | When a polynomial P(x) is divided by (x - a), the remainder is P(a). |
Synthetic Division | A shortcut method for polynomial division to find quotients and remainders. |
Rational Function | A function that can be expressed as the quotient of two polynomials. |
Partial Fractions | Breaking down a rational function into a sum of simpler fractions. |
Matrix | A rectangular array of numbers, symbols, or expressions arranged in rows and columns. |
Order of a Matrix | The number of rows and columns in a matrix. |
Scalar Multiplication | Multiplying a matrix by a single number (scalar), multiplies every element of the matrix. |
Matrix Addition and Subtraction | Combining or subtracting corresponding elements of two matrices. |
Matrix Multiplication | A defined operation where the product of two matrices is obtained by multiplying rows and columns. |
Identity Matrix | A square matrix with ones on the diagonal and zeros elsewhere. |
Transpose of a Matrix | Interchanging rows and columns of a matrix. |
Symmetric Matrix | A square matrix that is equal to its transpose. |
The inverse of a Matrix | A matrix that, when multiplied by the original matrix, gives the identity matrix. |
Cramer's Rule | A method for solving a system of linear equations using determinants. |
System of Linear Equations | A set of equations with multiple variables, all of which are linear. |
Consistent and Inconsistent Systems | A system of equations is consistent if it has at least one solution and inconsistent if it has none. |
Leontief Input-Output Model | A mathematical model used to analyze economic relationships and interdependencies between industries. |
In CBSE Class 12 Applied Mathematics Algebra, you'll encounter various matrices. Let's delve into each of these types with explanations:
The properties of scalar multiplication in algebra for matrices are as follows:
Let A and B be two matrices of the same order (m × n), and let k and p be scalars.
(i) Scalar Multiplication Distributes Over Matrix Addition:
This property means that you can distribute a scalar (k) across the sum of two matrices (A and B) by multiplying each matrix by the scalar individually.
(ii) Scalar Addition Distributes Over Matrix Multiplication:
This property states that you can distribute the sum of two scalars (k and p) across a matrix (A) by multiplying the matrix by each scalar individually.
(iii) Scalar Multiplication Distributes Over Matrix Subtraction:
Similar to property (i), you can distribute a scalar (k) across the difference of two matrices (A and B) by multiplying each matrix by the scalar individually.
The properties of addition of matrices in algebra are as follows:
i) Addition of Matrices with the Same Order:
ii) Commutative Property of Matrix Addition:
iii) Associative Property of Matrix Addition:
iv) Zero Matrix is the Additive Identity:
v) Additive Inverse or Negative of a Matrix:
The properties of multiplication of matrices in algebra are as follows:
i) Associative Property of Matrix Multiplication:
ii) Distributive Property of Matrix Multiplication over Addition and Subtraction:
iii) Existence of Multiplicative Identity (Identity Matrix):
The properties of the adjoint (also known as the adjugate or classical adjoint) of a square matrix A of order n are as follows:
i) Product of a Matrix and Its Adjoint:
ii) Determinant of the Adjoint Matrix:
The transpose of a matrix is an operation that flips the matrix over its main diagonal, which is the line from the top-left to the bottom-right corner.
This operation changes the matrix rows into columns and the columns into rows. The result is a new matrix with dimensions swapped, i.e., if the original matrix is of order m × n, the transpose will be of order n × m.
Mathematically, if you have a matrix A of order m × n, its transpose (denoted as A^T or simply A with a superscript "T") is obtained as follows:
If A = [a_ij], then A^T = [b_ij], where b_ij = a_ji.
In other words, each element in the original matrix's i-th row and j-th column becomes the transposed matrix's j-th row and i-th column element.
The properties of the transpose of a matrix are as follows:
i) Double Transpose Property:
ii) Scalar Multiplication and Transpose:
iii) Addition and Transpose:
iv) Multiplication and Transpose (Reverse Order):
To help you better understand the type of questions asked from the algebra topic, we have provided a few sample questions here.
Question 1: Under what conditions on the real numbers a, b, c, d, e, f do the simultaneous equations ax + by = e and cx + dy = f have (a) a unique solution, (b) no solution, (c) infinitely many solutions in x and y. Select values of a, b, c, d, e, f for each case, and sketch the lines ax+by = e and cx+dy = f on separate axes.
Question 2: For what values of a do the simultaneous equations x + 2y + a2z = 0, x + ay + z = 0, x + ay + a2z = 0 have a solution other than x = y = z = 0. For each such find the general solution of the above equations.
Question 3: Do 2 × 2 matrices exist satisfying the following properties? Either find such matrices or show that no such exists.
Question 4: (a) Find the remainder when n2 + 4 is divided by 7 for 0 ≤ n < 7. Deduce that n2 + 4 is not divisible by 7, for every positive integer n. [Hint: write n = 7k + r where 0 ≤ r < 7.] (b) Now k is an integer such that n3 + k is not divisible by 4 for all integers n. What are the possible values of k?
Certainly, here's a table outlining common errors students might encounter when solving CBSE Class 12 Applied Mathematics Algebra problems and how to avoid them:
Common Error | How to Avoid It |
---|---|
Not Paying Attention to Matrix Order | Always check the order of matrices before performing operations like addition, subtraction, or multiplication. Ensure that the order is compatible with the operation you're performing. |
Misinterpreting Matrix Dimensions | Be careful when interpreting matrices. Rows and columns matter. For instance, don't confuse a row matrix with a column matrix or a square matrix with a rectangular matrix. |
Overlooking Matrix Multiplication Rules | Remember that the order of multiplication matters in matrix multiplication. (AB ≠ BA in general). Pay attention to the dimensions of the matrices to be multiplied. |
Ignoring Identity and Zero Matrices | Understand the properties of identity and zero matrices, and use them appropriately in calculations. Know how they affect operations and equations. |
Inconsistent Use of Notation | Maintain consistent notation throughout your work. Use the same symbols and conventions for matrices, variables, and operations. |
Incorrectly Computing Determinants | Practice calculating determinants correctly using methods like the Sarrus Rule or cofactor expansion. Pay attention to signs and arithmetic. |
Not Checking for Equal Matrices | When comparing matrices, ensure that they have the same order and that each element matches. Don't assume equality without verifying it. |
Misunderstanding Diagonal Matrices | Remember that diagonal matrices have non-zero values only on the main diagonal. Ensure other entries are zero. |
Confusing Row Matrices with Scalars | Differentiate between row matrices and scalar multiples. Don't treat a row matrix as a scalar or vice versa. |
Skipping Steps in Linear Programming | Follow a systematic approach in linear programming problems. Clearly define objectives, constraints, and the feasible region. Don't skip key steps. |
Not Double-Checking Calculations | Take time to double-check your calculations, especially when dealing with complex expressions or large matrices. A small arithmetic error can lead to incorrect results. |
In CBSE Class 12 Applied Mathematics Algebra, a comprehensive understanding of matrices, determinants, and their properties is crucial for success.
These topics constitute a significant portion of the syllabus and play a vital role in various mathematical applications. To excel in this subject, students should:
Frequently Asked Questions
What is the weightage of Algebra section in Applied maths subject of class 12?
What are the topics which will be taught in Applied Maths Algebra section class 12?
What are the best reference books for the CBSE class 12 Applied Maths Subject?
Which Mathematics is tougher, the pure one or the Applied one?
What is the importance of studying algebra in CBSE Class 12 Applied Mathematics?
What are the main topics covered in the CBSE Class 12 Applied Mathematics Algebra syllabus?
How can I determine if a system of linear equations has a unique solution, no solution, or infinitely many solutions?
Q5: What is the significance of the identity matrix in algebra?
How does scalar multiplication work in matrix algebra?