Definitions [2]
A determinant is a number associated with a square matrix.
\[\begin{vmatrix}
a & b \\
c & d
\end{vmatrix}=ad-bc\]
The value of the determinant is ad - bc.
The degree of a 2 × 2 determinant is 2.
Cramer’s Rule is a method to solve simultaneous linear equations using determinants.
-
It can be applied only when the determinant D ≠ 0
- Standard Form of Equations
a2x + b2y = c2
Formulae [1]
\[D=
\begin{vmatrix}
a_1 & b_1 \\
a_2 & b_2
\end{vmatrix}=a_1b_2-a_2b_1\]
\[D_x=
\begin{vmatrix}
c_1 & b_1 \\
c_2 & b_2
\end{vmatrix}=c_1b_2-c_2b_1\]
\[D_y=
\begin{vmatrix}
a_1 & c_1 \\
a_2 & c_2
\end{vmatrix}=a_1c_2-a_2c_1\]
\[x=\frac{D_x}{D}\quad\mathrm{and}\quad y=\frac{D_y}{D}\]
-
If D ≠ 0 → unique solution
-
If D = 0 → Cramer’s rule is not applicable
Theorems and Laws [1]
Prove that the determinant `|(x,sin theta, cos theta),(-sin theta, -x, 1),(cos theta, 1, x)|` is independent of θ.
Let, Δ = `|(x,sintheta,costheta),(-sintheta,-x,1),(costheta,1,x)|`
= x(−x2 − 1) − sin θ(−x sin θ − cos θ) + cos θ(−sin θ + x cos θ)
= −x(x2 + 1) + x sin2 θ + sin θ cos θ − sin θ cos θ + x cos2 θ
= −x(x2 + 1) + x(sin2 θ + cos2 θ)
= −x(x2 + 1) + x
= −x[x2 + 1 − 1]
= −x3
Hence, the determinant is independent of θ.
Key Points
| Property | Rule / Statement |
|---|---|
| Compatibility Rule | Matrices A and B can be multiplied only if the columns of A = the rows of B |
| Order of Product | If A is m × n and B is n × p, then AB is m × p |
| Non-Commutative | AB `\cancel(=)` BA (in general) |
| Associative Property | A(BC) = (AB)C |
| Distributive over Addition | A(B + C) = AB + AC |
| Zero Matrix Property | The product of two non-zero matrices can be a zero matrix |
| Cancellation Law | If AB = AC, it does not imply B = C |
| Identity Matrix | AI = IA = A (orders compatible) |
Concepts [11]
- Determinant Method (Cramer’s Rule)
- Determinant of a Matrix
- Determinants of Matrix of Order One and Two
- Determinant of a Matrix of Order 3 × 3
- Properties of Determinants
- Application of Determinants
- Area of a Triangle Using Determinants
- Minors and Co-factors
- Adjoint of a Matrix
- Properties of Matrix Multiplication
- Applications of Determinants and Matrices
