Definitions [8]
A determinant is a single real number associated with a square matrix only.
- Denoted by det A or ∣A∣ or Δ
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.
Consistent Solution: A system is consistent if it has at least one solution.
Inconsistent Solution: A system is inconsistent if it has no solution.
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
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.
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.
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 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]
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
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
| 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 |
-
Area of triangle using determinant:
-
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.
-
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 \[i \neq k\].
- adj (AB) = (adj B) (adj A)
- (adj A)A = A (adj A) = |A| Iₙ
- (a) |adj A| = |A|ⁿ⁻¹, if |A| ≠ 0
(b) |adj A| = 0, if |A| = 0 - If |A| = 0, then (adj A) A = A (adj A) = O
- adj (Aᵐ) = (adj A)ᵐ, m ∈ N
- adj (kA) = kⁿ⁻¹ (adj A), k ∈ R
- adj (adj A) = |A|ⁿ⁻² A, A is non-singular matrix
- adj (adj A) = |A|ⁿ⁻² A, A is non-singular matrix
-
Area of triangle using determinant:
-
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.
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
-
(adjA)B ≠ 0 → no solution
Homogeneous system:
AX = 0
-
Always consistent
-
∣A∣ ≠ 0 → trivial solution
-
∣A∣ = 0→ infinitely many solutions
Applicable ONLY for 3×3 determinants
Steps:
-
Rewrite the first two columns to the right
-
Add products of downward diagonals
-
Subtract products of upward diagonals
Important Questions [3]
- If a = Matrix ((2,3,10),(4,-6,5),(6,9,-20))`, Find `A Power (-1)`. Using `Apower(-1) Solve the System of Equation 2byx + 3byy +10/Z = 2`;`4by - 6byy + 5byz = 5`; 6byx + 9byy - 20byz = -4`
- If a = ⎡ ⎢ ⎣ 5 6 − 3 − 4 3 2 − 4 − 7 3 ⎤ ⎥ ⎦ , Then Write the Cofactor of the Element A21 of Its 2nd Row.
- If a = ⎡ ⎢ ⎣ 1 1 1 1 0 2 3 1 1 ⎤ ⎥ ⎦ , Find A-1. Hence, Solve the System of Equations X + Y + Z = 6, X + 2z = 7, 3x + Y + Z = 12.
