Matrix Mastery

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Questions and Answers

Which type of matrix has M ≠ N?

  • Unit matrix
  • Square matrix
  • Rectangular matrix (correct)
  • Null matrix

What is a submatrix?

  • A matrix with only one row or one column
  • A matrix obtained by eliminating some rows and/or columns from a given matrix (correct)
  • A square submatrix with diagonal elements equal to one
  • A matrix with all elements equal to zero

What is the unit matrix?

  • A matrix with all elements equal to zero
  • A square submatrix with diagonal elements equal to one
  • A square matrix with all principal diagonal elements equal to one and all other elements equal to zero (correct)
  • A matrix with only one row or one column

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Study Notes

Introduction to Matrices: Basics and Types

  • Matrices are important in GATE exams, with at least one fashion and sometimes two questions on the topic.
  • A matrix is a two-dimensional array that is represented as "M x N," where M is the number of rows and N is the number of columns.
  • Rectangular matrices have M ≠ N, while square matrices have M = N.
  • The unit matrix is a square matrix with all principal diagonal elements equal to one and all other elements equal to zero.
  • The null matrix is a matrix in which all elements are zero.
  • Row matrices have only one row, while column matrices have only one column.
  • A submatrix is obtained by eliminating some rows and/or columns from a given matrix.
  • The principal submatrix is a square submatrix in which the principal diagonal elements also occur in the principal diagonal of the original matrix.
  • From a square matrix, if exactly one row and one column are eliminated, the resulting matrix is also a square matrix.
  • The resulting submatrix is a principal submatrix if its principal diagonal elements also occur in the principal diagonal of the original matrix.
  • Not all combinations of eliminated rows and columns will result in a principal submatrix.
  • The properties of matrices are important for matrix operations such as finding the matrix inverse and matrix multiplication.

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