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MathsMediumClass 12

Types — Symmetric, skew-symmetric, orthogonal

Matrices

6

JEE Qs

8%

Hard

45

min

Thoroughly understand the properties of transpose and matrix multiplication, as they are fundamental to identifying and manipulating symmetric, skew-symmetric, and orthogonal matrices in problem-solving.

🧮 Key Formulas

A is Symmetric if A^T = A
A is Skew-Symmetric if A^T = -A
Any square matrix A can be uniquely expressed as A = P + Q, where P = (1/2)(A + A^T) (Symmetric) and Q = (1/2)(A - A^T) (Skew-Symmetric)
A is Orthogonal if A^T A = I and A A^T = I (where I is the identity matrix)
If A is Orthogonal, then det(A) = +/- 1

✅ Key Points for JEE

  • 1For a symmetric matrix A, the elements satisfy a_ij = a_ji for all i, j. The diagonal elements can be any real number.
  • 2For a skew-symmetric matrix A, the elements satisfy a_ij = -a_ji for all i, j. This implies that all diagonal elements (a_ii) must be zero.
  • 3If A is an orthogonal matrix, its inverse A^(-1) is simply its transpose A^T. This significantly simplifies finding inverses.
  • 4The sum/difference of two symmetric matrices is symmetric. The sum/difference of two skew-symmetric matrices is skew-symmetric.
  • 5The determinant of an orthogonal matrix is always +1 or -1. This can be used as a quick check for orthogonality or to solve problems involving orthogonal matrices.

⚠️ Common Mistakes

  • Confusing the definitions of symmetric (A^T = A) and skew-symmetric (A^T = -A) matrices.
  • Incorrectly assuming diagonal elements of a symmetric matrix are zero (only true for skew-symmetric matrices).
  • Errors in matrix multiplication when verifying the orthogonality condition A^T A = I.
  • Forgetting that (AB)^T = B^T A^T when dealing with products of matrices and their transposes.

NCERT Chapters

  • Class 12 Mathematics Ch 3: Matrices