CBSE Class 12 Applied Maths Algebra 2025-26, Syllabus and Tips

CBSE Class 12 Applied Maths Algebra: In response to the increasing demand for practical mathematics skills in today's fast-paced business world, CBSE has introduced a new elective course called Class 12 Applied Maths.

CBSE Class 12 Applied Maths Algebra

CBSE Class 12 Applied Maths Algebra Syllabus

To excel in your Applied Mathematics Algebra studies for CBSE Class 12 Commerce , it's crucial to understand key topics such as Matrices, Determinants, Cramer’s rule, and their practical applications. This includes learning about the Leontief input-output model for two variables. Familiarizing yourself with the syllabus will guide your focus towards these important areas, ultimately helping you achieve better scores in your exams. Here's a breakdown of the CBSE Class 12 Applied Maths Algebra syllabus for 2025-26:

CBSE Class 12 Applied Maths Algebra Important Definitions

• Algebra : It's a math branch handling symbols and rules to work with them.
• Polynomial : A mix of variables, coefficients, and exponents with mathematical operations.
• Degree of a Polynomial : The highest exponent of a variable within a polynomial.
• Zero of a Polynomial : A value making a polynomial equal to zero.
• Factorization : Breaking down a polynomial into other polynomials' products.
• Factor Theorem : States if (x - a) is a polynomial factor, then P(a) equals zero.
• Remainder Theorem : When dividing a polynomial by (x - a), the remainder equals P(a).
• Synthetic Division : A quick way to divide polynomials to find quotients and remainders.
• Rational Function : A function represented as a fraction of two polynomials.
• Partial Fractions : Splitting a rational function into simpler fractions.
• Matrix : A grid of numbers, symbols, or expressions in rows and columns.
• Order of a Matrix : The count of rows and columns in a matrix.
• Scalar Multiplication : Multiplying every matrix element by a single number.
• Matrix Addition/Subtraction : Adding/subtracting corresponding elements of two matrices.
• Matrix Multiplication : A defined operation, combining rows and columns of two matrices.
• Identity Matrix : A square matrix with ones on its diagonal and zeros elsewhere.
• Transpose of a Matrix : Switching rows and columns of a matrix.
• Symmetric Matrix : A square matrix equal to its transpose.
• Matrix Inverse : A matrix, when multiplied with the original, yields the identity matrix.
• Cramer's Rule : Solving linear equations systems using determinants.
• System of Linear Equations : A set of linear equations with multiple variables.
• Consistent/Inconsistent Systems : Consistent systems have at least one solution; inconsistent ones have none.
• Leontief Input-Output Model : A math model examining economic relationships among industries.

Common Errors While Solving CBSE Class 12 Applied Maths Algebra

1. Check Matrix Order: Before adding, subtracting, or multiplying matrices, always ensure their orders match.
2. Understand Matrix Dimensions: Be clear on the difference between row and column matrices, as well as square and rectangular matrices.
3. Remember Matrix Multiplication Rules: The order of multiplication is crucial in matrix math. Pay attention to matrix dimensions.
4. Use Identity and Zero Matrices Correctly: Know how identity and zero matrices affect calculations.
5. Maintain Consistent Notation: Keep your notation uniform throughout your work.
6. Compute Determinants Accurately: Practice calculating determinants correctly and watch out for signs and arithmetic errors.
7. Verify Matrices for Equality: Make sure matrices you're comparing have the same order and all elements match.
8. Understand Diagonal Matrices: Diagonal matrices have non-zero values only on the main diagonal.
9. Differentiate Between Row Matrices and Scalars: Be clear on the distinction between row matrices and scalar multiples.
10. Follow Steps in Linear Programming: Don't skip key steps in linear programming problems.
11. Double-Check Calculations: Always take a moment to review your calculations, especially with complex expressions or large matrices.

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