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Revision: Algebra >> Determinants Maths Commerce (English Medium) Class 12 CBSE

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Definitions [7]

Definition: Determinant

A determinant is a single real number associated with a square matrix only.

  • Denoted by det ⁡A or ∣A∣ or Δ 
Definition: Expansion Method

To find the determinant, multiply each element of your chosen row (or column) by its corresponding sign multiplier \[(-1)^{i+j}\] and the \[2 \times 2\] determinant that remains after deleting that element's row and column.

Definition: Minor

Let A = [aij] be a square matrix of order n. Then, the minor Mij of aij in A is the determinant obtained by deleting the ith row and the jth column in which element aij lies. It is denoted by Mij​ of A.

Definition: Co-factors

Let A = [aij] be a square matrix of order n. Then, the cofactor Cij (or Aij) of aij in A is (−1)i+j times Mij, where Mij is the minor of aij in A.

∴ Cij = (−1)i+j Mij

Definition: Inverse of a Matrix

If A and B are non-singular square matrices of the same order such that AB = BA = I (where I is the identity matrix of the same order as A and B), then A and B are called inverses of each other.

We write A⁻¹ = B and B⁻¹ = A.

i.e. AA⁻¹ = A⁻¹A = I.

  • If |A| ≠ 0, then A⁻¹ exists.
  • If the inverse of a square matrix exists, then it is unique. A matrix can not have more than one distinct inverse.
Definition: Adjoint of a Matrix

The adjoint of A is defined as the transpose (i.e. interchange rows and columns) of the cofactor matrix, and it is denoted by adj (A).

Consistent and Inconsistent

Consistent Solution: A system is consistent if it has at least one solution.

Inconsistent Solution: A system is inconsistent if it has no solution.

Formulae [3]

Formula: Determinant of a Matrix

Order 1 (1×1 matrix):

∣A∣ = a

Order 2 (2×2 matrix):

∣A∣ = ad − bc

Order 3 (3×3 matrix):

\[A= \begin{bmatrix} a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33} \end{bmatrix}\]

\[|A|=a_{11}(a_{22}a_{33}-a_{32}a_{23})-a_{12}(a_{21}a_{33}-a_{31}a_{23})+a_{13}(a_{21}a_{32}-a_{31}a_{22})\]

  • If |A| = 0
    A matrix is called a Singular Matrix
  • If |A| ≠ 0
    Matrix is called a Non-Singular Matrix
Formula: Expansion
For a matrix A, expanding along the first row (\[R_1\]) looks like this:
\[|A| = (-1)^{1+1} a_{11} \begin{vmatrix} a_{22} & a_{23} \\ a_{32} & a_{33} \end{vmatrix} + (-1)^{1+2} a_{12} \begin{vmatrix} a_{21} & a_{23} \\ a_{31} & a_{33} \end{vmatrix} + (-1)^{1+3} a_{13} \begin{vmatrix} a_{21} & a_{22} \\ a_{31} & a_{32} \end{vmatrix}\]
 
Invariance: Expanding the determinant along any row (e.g., \[R_1, R_2, R_3\]) or any column (\[C_1, C_2, C_3\]) will always yield the exact same final value.
Formula: Inverse of a Square Matrix

By Adjoint Method: \[A^{-1}=\frac{\mathrm{adj}A}{|A|}\]

By Using Algebraic Equation: A matrix A and an algebraic equation in matrix A is in the form of A² + bA + C = O.

\[A^{-1}=\frac{1}{C}\left[-aA-bI\right]\]

Key Points

Key Points: Expansion of Determinant
Concept Formula/Rule
Expansion along R₁ a₁₁C₁₁ + a₁₂C₁₂ + a₁₃C₁₃
Expansion along C₁ a₁₁C₁₁ + a₂₁C₂₁ + a₃₁C₃₁
Cofactor Sign (-1)(i+j) → checkerboard: + - + / - + - / + - +
Zero Strategy Expand along row/column with most zeros
Result Independence Any row/column expansion gives same
Key Points: Area of Triangle using Determinant
  • Area of triangle using determinant:

\[ \frac{1}{2} \begin{vmatrix} x_1 & y_1 & 1 \\ x_2 & y_2 & 1 \\ x_3 & y_3 & 1 \end{vmatrix}\]
  • Expanded coordinate form:

    \[\text{Area} = \frac{1}{2}|x_1(y_2 - y_3) + x_2(y_3 - y_1) + x_3(y_1 - y_2)|\].

  • Area is always taken as positive; use absolute value.

  • For collinear points, determinant = 0, so area = 0.

Key Points: Minors and Co-factors
  • Minor \[M_{ij}\]: determinant of the matrix obtained by deleting row i and column j.

  • Cofactor \[C_{ij}\]: \[C_{ij} = (-1)^{i+j}M_{ij}\].

  • Determinant expansion along row i: \[|A| = \sum_{j=1}^{n} a_{ij}C_{ij}\].

  • Determinant expansion along column j: \[|A| = \sum_{i=1}^{n} a_{ij}C_{ij}\].

  • Determinant value is the same for any choice of row or column for expansion.

  • Mixed row/column property: \[\sum_{j=1}^{n} a_{ij}C_{kj} = 0\] for \[i \neq k\].

Key Points: Adjoint of a Matrix
  1. adj (AB) = (adj B) (adj A)
  2. (adj A)A = A (adj A) = |A| Iₙ
  3. (a) |adj A| = |A|ⁿ⁻¹, if |A| ≠ 0
    (b) |adj A| = 0, if |A| = 0
  4. If |A| = 0, then (adj A) A = A (adj A) = O
  5. adj (Aᵐ) = (adj A)ᵐ, m ∈ N
  6. adj (kA) = kⁿ⁻¹ (adj A), k ∈ R
  7. adj (adj A) = |A|ⁿ⁻² A, A is non-singular matrix
  8. adj (adj A) = |A|ⁿ⁻² A, A is non-singular matrix
Key Points: Solution of Linear Equations using Determinants

System of linear equations: AX = B

Consistent / Inconsistent:

  • Consistent → one or more solutions

  • Inconsistent → no solution

Matrix method (Martin’s Rule):

If ∣A∣ ≠ 0, X = A−1B ⇒ unique solution

When ∣A∣ = 0:

  • → infinitely many solutions

  • (adj⁡A)B ≠ 0 → no solution

Homogeneous system:

AX = 0

  • Always consistent

  • ∣A∣ ≠ 0 → trivial solution

  • ∣A∣ = 0→ infinitely many solutions

Key Points: Rule of Sarrus

Applicable ONLY for 3×3 determinants

Steps:

  1. Rewrite the first two columns to the right

  2. Add products of downward diagonals

  3. Subtract products of upward diagonals

Important Questions [16]

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