If you are looking for a Plus Two Focus Area Notes for all Subjects PDF, then you are in the right place. At the end of this post, we have added a button to directly download the PDF of Kerala Plus Two Focus Area Chapter-wise Notes for free.
Plus Two Focus Area Malayalam
Here we have shared the Plus Two Focus Area Syllabus. Below mentioned is the Plus 2 Focus Area Syllabus of Maths. Please note that the Maths Syllabus for Commerce and Science Stream may vary.
| Chapters | Focus area |
|---|---|
| RELATIONS AND FUNCTIONS | 1.2 Types of Relations 1.3 Types of Functions 1.4 Composition of Functions and Invertible Function |
| INVERSE TRIGONOMETRIC FUNCTIONS | 2.3 Properties of Inverse Trigonometric Functions |
| MATRICES | 3.2 Matrix 3.3 Types of Matrices 3.4 Operations on Matrices 3.5 Transpose of a Matrix 3.6 Symmetric and Skew Symmetric Matrices |
| DETERMINANTS | 4.2 Determinant 4.4 Area of a Triangle. 4.5 Minors and Cofactors 4.6 Adjoint and Inverse of a Matrix 4.7 Applications of Determinants and Matrices |
| CONTINUITY AND DIFFERENTIABILITY | 5.2 Continuity 5.3 Differentiability 5.6 Derivatives of Functions in Parametric Forms 5.8 Mean Value Theorem |
| APPLICATION OF DERIVATIVES | 6.2 Rate of Change of Quantities 6.3 Increasing and Decreasing Functions 6.4 Tangents and Normals |
| INTEGRALS | 11.3 Equation of a Line in Space 11.5.1 Distance between skew lines 11.6.2 Equation of a plane perpendicular to a given vector and passing through a given point. 11.6.3 Three-point form |
| APPLICATION OF INTEGRALS | 8.2 Area under Simple Curves |
| DIFFERENTIAL EQUATIONS | 7.3.1 integration by substitution 7.4 Integrals of Some Particular Functions 7.5 Integration by Partial Fractions 7.6 Integration by Parts and 7.6.1 7.9 Evaluation of Definite Integrals by Substitution |
| VECTOR ALGEBRA | 10.4 Addition of Vectors 10.5 Multiplication of a Vector by a Scalar 10.6 Product of Two Vectors |
| THREE DIMENSIONAL GEOMETRY | 13.2 Conditional Probability 13.4 independent Events 13.5 Bayes’ Theorem 13.6 Random variables and their probability distributions. |
| LINEAR PROGRAMMING | 12.2. Linear programming problem and its mathematical formulation. |
| PROBABILITY | 13.2 Conditional Probability 13.4 independent Events 13.5 Bayes’ Theorem 13.6 Random variables and its probability distributions. |
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