How Do You Calculate the Determinant of a Matrix in Linear Algebra?

In summary, the conversation discusses the question of how to solve a mathematical problem involving the determinant of a matrix. The answer is determined to be -30, with the help of a linked article that explains how both row and column operations can be used to solve the problem. The confusion is cleared up with the assistance of other individuals involved in the conversation.
  • #1
Chipset3600
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Hello guys, can someone help me with this question please?

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  • #3
pickslides said:
The answer could be -30.

This article may be helpful

http://science.kennesaw.edu/~plaval/math3260/det2.pdf

What the linked document says about row operations also applies to column operations as the determinant of the transpose is equal to the determinant. It is both row and coumn operations that are needed here (or switching between the matrix and its transpose, which is the same thing).

CB
 
  • #4
pickslides and CaptainBlack, the problem was that i throug the theorem of Jacobi was only for rows, than i was thinking how he got the "5" in second column. thank you guys!
 
  • #5


Sure, I can help you with your question about determinants in linear algebra. A determinant is a mathematical value that can be calculated for a square matrix. It represents the scaling factor of the matrix, and is used in various applications such as solving systems of linear equations, calculating areas and volumes, and finding the inverse of a matrix.

To calculate the determinant of a matrix, you can use various methods such as the cofactor expansion or Gaussian elimination. The determinant of a 2x2 matrix can be found by multiplying the elements along the main diagonal and subtracting the product of the elements along the other diagonal. For larger matrices, the calculation can be more complex.

Determinants have many important properties, such as being equal to zero if the matrix is singular (meaning it has no inverse), and being equal to the product of the eigenvalues if the matrix is diagonalizable. They are also useful in solving systems of linear equations, as the determinant can determine whether the system has a unique solution, no solution, or infinitely many solutions.

I hope this helps to answer your question about determinants in linear algebra. Let me know if you have any further questions or need clarification on anything.
 

Related to How Do You Calculate the Determinant of a Matrix in Linear Algebra?

What is a determinant?

A determinant is a special value that can be calculated for a square matrix. It is represented by the vertical bars on either side of the matrix and is used to determine various properties of the matrix, such as whether it is invertible or singular.

How do you calculate a determinant?

To calculate a determinant, you must first make sure the matrix is a square matrix. Then, you can use various methods such as the cofactor expansion method or the Gaussian elimination method to find the determinant.

What is the significance of the determinant?

The determinant of a matrix has several important applications in linear algebra. It is used to determine the invertibility of the matrix, the number of solutions to a system of linear equations, and the area or volume of a parallelogram or parallelepiped defined by the vectors in the matrix.

Can a determinant be negative?

Yes, a determinant can be negative. The sign of the determinant is determined by the number of row swaps performed during the calculation. If there are an odd number of row swaps, the determinant will be negative, and if there are an even number of row swaps, the determinant will be positive.

What is the relationship between determinants and eigenvalues?

The determinant of a matrix can be used to calculate its eigenvalues. The eigenvalues of a matrix are the values that, when multiplied by the identity matrix and subtracted from the original matrix, result in a matrix with a determinant of 0. This relationship is important in many applications of linear algebra, such as solving systems of differential equations.

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