1. Introduction
Matrices are frequently used in all branches of science and engineering. They play an important role especially
in solving engineering problems due to their special ability. One of the important abilities associated with
matrices is data classification, by which many problems are solved by computers. Naturally, the important
part of the solution process by matrices in computers is algebraic analysis.
In this process, we use inversing matrices in linear equations and so on. For this purpose, it is necessary to
find determinant of matrices. Determinants are useful in many areas of mathematics. They can be used to
solve systems of linear equations. A matrix is singular if and only if its determinant is zero. A matrix with
a determinant close to zero is close to being singular. This can cause a large error in calculations that requires
an inverse. If a matrix defines a linear transformation from N dimensional space to N dimensional space, then
the determinant of that matrix has some interesting properties. If one uses a matrix to transform all the points
inside some bounded space (e.g. in one dimensional space all the points between two end points, or in two
dimensional space all the points inside a rectangle or circle or some other shape, etc.) after the transformation
the points will again fill a closed space. The area, volume etc. in a higher dimensional space (a general term is
‘‘measure’’) will have changed by a factor. It is equal to the determinant of the transformation matrix. The
sign indicates the direction of the points. For example, when transforming points on the edge of a circle,