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Mathematics XII · High-Weightage Topics

5-Mark Concept Guide

Important theorems, proofs, and long-answer patterns for CBSE board exam preparation.

13
Chapters
80
Marks total
11
High-weight chapters

High-Weightage Chapters

🎯 These chapters carry the most marks β€” prepare these first:

  1. Ch 5: Continuity and Differentiability β€” 8 marks
  2. Ch 6: Application of Derivatives β€” 8 marks
  3. Ch 7: Integrals β€” 8 marks
  4. Ch 13: Probability β€” 8 marks
πŸ“ Ch 3: Matrices
5 marks
  • Theorem 1
    For any square matrix A with real number entries, A + A' is a symmetric matrix and A - A' is a skew symmetric matrix.
  • Theorem 2
    Any square matrix can be expressed as the βˆ‘ of a symmetric and a skew symmetric matrix. Specifically, A = (1/2)(A + A') + (1/2)(A - A').
  • Theorem 3 (Uniqueness of inverse)
    Inverse of a square matrix, if it exists, is unique.
  • Matrices simplify work compared to straightforward methods
  • Matrices represent coefficients ∈ systems of linear equations
  • Matrix notation is used ∈ electronic spreadsheet programs
  • We follow the notation A = [aα΅’β±Ό]β‚˜ β‚“ β‚™ to indicate that A is a matrix of order m x n
πŸ“ Ch 4: Determinants
5 marks
  • Theorem 1
    If A be any given square matrix of order n, then A(adj A) = (adj A)A = |A|*I, where I is the identity matrix of order n.
  • Theorem 2
    If A and B are nonsingular matrices of the same order, then AB and BA are also nonsingular matrices of the same order.
  • Theorem 3
    The determinant of the ∏ of matrices is equal to ∏ of their respective determinants, that is, |AB| = |A| Β· |B|, where A and B are square matrices of t…
  • Determinants have wide applications ∈ Engineering, Science, Economics, Social Science, etc.
  • In this chapter, determinants up to order three with real entries only are studied
  • Topics covered: properties of determinants, minors, cofactors, applications ∈ finding area of triangle, adjoint and inverse of a square matrix, consistency and inconsistency of systems, solution using inverse of a matrix
  • For matrix A, |A| is read as determinant of A and not modulus of A
πŸ“ Ch 5: Continuity and Differentiability
8 marks
  • Theorem 1
    Suppose f and g be two real functions continuous at a real number c. Then: (1) f + g is continuous at x = c, (2) f - g is continuous at x = c, (3) f .…
  • Theorem 2 (Composition)
    Suppose f and g are real valued functions such that (f o g) is defined at c. If g is continuous at c and if f is continuous at g(c), then (f o g) is c…
  • Theorem 3
    If a function f is differentiable at a point c, then it is also continuous at that point.
  • Previously learnt to differentiate polynomial and trigonometric functions
  • This chapter connects continuity and differentiability
  • Powerful techniques of differentiation are developed
  • f is continuous at x = c if: (1) f(c) is defined, (2) lim(x->c) f(x) exists, (3) lim(x->c) f(x) = f(c)
πŸ“ Ch 6: Application of Derivatives
8 marks
  • First Derivative Test for Increasing/Decreasing
    Let f be continuous on [a, b] and differentiable on (a, b). Then: (a) f is increasing ∈ [a,b] if f'(x) β‰₯ 0 for each x ∈ (a,b) ┃ (b) f is decreasing ∈ …
  • Necessary condition for local extrema
    Let f be a function defined on an open interval I. Suppose c is ∈ I. If f has a local maxima or a local minima at x = c, then either f'(c) = 0 or f is…
  • First Derivative Test
    Let f be a function defined on an open interval I. Let f be continuous at a critical point c ∈ I. Then: (i) If f'(x) changes sign from positive to neg…
  • Chapter 5 covered finding derivatives; this chapter covers applications of those derivatives
  • Applications include: (i) rate of change, (ii) tangent and normal equations, (iii) turning points for maxima/minima, (iv) increasing/decreasing intervals, (v) approximations
  • dy/dx is positive if y increases as x increases
  • dy/dx is negative if y decreases as x increases
πŸ“ Ch 7: Integrals
8 marks
  • First Fundamental Theorem of Integral Calculus
    Let f be a continuous function on the closed interval [a, b] and let A(x) be the area function. Then A'(x) = f(x), for all x ∈ [a, b].
  • Second Fundamental Theorem of Integral Calculus
    Let f be continuous function defined on the closed interval [a, b] and F be an anti derivative of f. Then ∫ from a to b of f(x) dx = [F(x)] from a to …
  • Integration is the inverse process of differentiation.
  • Integral calculus was developed to solve problems of finding functions from derivatives and finding areas under curves.
  • d/dx[∫ f(x) dx] = f(x) and ∫ f'(x) dx = f(x) + C: differentiation and integration are inverses of each other.
  • Two indefinite integrals with the same derivative lead to the same family of curves and so they are equivalent.
πŸ“ Ch 8: Application of Integrals
5 marks
  • Application of definite integrals to find area under curves is a specific use of integration as the limit of a βˆ‘.
  • We also find the area bounded by the above said curves.
  • If the curve lies below the x-axis, the definite ∫ gives a negative value; take the absolute value for the area.
  • If the curve crosses the x-axis, split the ∫ at the crossing points and take absolute values of the negative parts.
πŸ“ Ch 9: Differential Equations
5 marks
  • An equation involving derivative(s) of the dependent variable with respect to independent variable(s) is called a differential equation.
  • x(dy/dx) + y = 0 is a differential equation because it involves a derivative of y with respect to x.
  • An ordinary differential equation involves derivatives with respect to only one independent variable.
  • 2(dΒ²y/dxΒ²) + (dy/dx)Β³ = 0 is an ordinary differential equation.
πŸ“ Ch 10: Vector Algebra
5 marks
  • Commutative Property of Vector Addition
    For any two vectors a and b: a + b = b + a
  • Associative Property of Vector Addition
    For any three vectors a, b, c: (a + b) + c = a + (b + c)
  • Cauchy-Schwarz Inequality
    For any two vectors a and b: |a . b| ≀ |a||b|
  • Scalars are real numbers representing magnitude only
  • Vectors have both magnitude and direction
  • This chapter covers basic concepts, operations on vectors, and their algebraic and geometric properties
  • Since the length is never negative, the notation |a| < 0 has no meaning
πŸ“ Ch 11: Three Dimensional Geometry
5 marks
  • In Class XI, Analytical Geometry ∈ two dimensions and introduction to three dimensional geometry used Cartesian methods only
  • This chapter uses vector algebra for 3D geometry
  • For any line, if a, b, c are direction ratios, then ka, kb, kc (k β‰  0) are also direction ratios
  • Any two sets of direction ratios of a line are proportional
πŸ“ Ch 12: Linear Programming
5 marks
  • Theorem 1 (Fundamental Theorem of Linear Programming)
    Let R be the feasible region (convex polygon) for a linear programming problem and let Z = ax + by be the objective function. When Z has an optimal va…
  • Theorem 2
    Let R be the feasible region for a linear programming problem, and let Z = ax + by be the objective function. If R is bounded, then the objective func…
  • In earlier classes, systems of linear equations and linear inequalities ∈ two variables were studied
  • Many applications ∈ mathematics involve systems of inequalities/equations
  • This chapter applies systems of linear inequalities/equations to solve real life problems
  • Example: A furniture dealer wanting to maximise profit from buying tables and chairs with investment and storage constraints
πŸ“ Ch 13: Probability
8 marks
  • Multiplication Theorem of Probability
    For any two events E and F: P(E ∩ F) = P(E) . P(F|E) = P(F) . P(E|F), provided P(E) β‰  0 and P(F) β‰  0.
  • Independence of Complements
    If E and F are independent events, then (a) E and F' are independent, (b) E' and F are independent, (c) E' and F' are independent.
  • Theorem of Total Probability
    Let {E₁, Eβ‚‚, ..., Eβ‚™} be a partition of the sample space S, and suppose that each of E₁, Eβ‚‚, ..., Eβ‚™ has nonzero probability of occurrence. Let A be a…
  • In earlier classes, probability was studied as a measure of uncertainty of events ∈ a random experiment
  • The axiomatic theory and the classical theory of probability are equivalent for equally likely outcomes
  • Throughout this chapter, experiments have equally likely outcomes unless stated otherwise
  • When event F is known to have occurred, the sample space reduces from S to F