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Solving a system of Linear Equations Using Inverse of a Matrix Part 2 Video Lecture | Mathematics (Maths) Class 12 - JEE

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00:03 Solving System of Linear Equations using Matrices
00:46 Inverse of a Matrix
01:01 Determinant of a Matrix
01:18 Adjoint of a Matrix
02:24 Multiplication of Matrices
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FAQs on Solving a system of Linear Equations Using Inverse of a Matrix Part 2 Video Lecture - Mathematics (Maths) Class 12 - JEE

1. What is the inverse of a matrix?
Ans. The inverse of a matrix is a matrix that, when multiplied by the original matrix, results in the identity matrix. It is denoted as A^-1, where A is the original matrix.
2. How can the inverse of a matrix be used to solve a system of linear equations?
Ans. To solve a system of linear equations using the inverse of a matrix, we can represent the system in matrix form as AX = B, where A is the coefficient matrix, X is the variable matrix, and B is the constant matrix. By finding the inverse of matrix A, we can multiply both sides of the equation by A^-1 to obtain X = A^-1 * B, which gives us the solution for the variables.
3. Are all matrices invertible?
Ans. No, not all matrices are invertible. A matrix is invertible (or non-singular) if and only if its determinant is non-zero. If the determinant is zero, the matrix is singular and does not have an inverse.
4. Can the inverse of a matrix be computed for any size of the matrix?
Ans. The inverse of a matrix can be computed for square matrices only, i.e., matrices that have an equal number of rows and columns. For non-square matrices, the inverse does not exist.
5. What happens if a matrix does not have an inverse?
Ans. If a matrix does not have an inverse, it is called a singular matrix. In the context of solving a system of linear equations, this means that the system either has no solution or infinitely many solutions, depending on the specific properties of the matrix.
Video Timeline
Video Timeline
arrow
00:03 Solving System of Linear Equations using Matrices
00:46 Inverse of a Matrix
01:01 Determinant of a Matrix
01:18 Adjoint of a Matrix
02:24 Multiplication of Matrices
More
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