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Last Updated Sep 27, 2025
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The size or dimension of a matrix is defined by the number of rows and columns it contains. If a matrix has rows and columns, it is referred to as an matrix.
Example: The matrix
has rows and columns, so it is a matrix.
The 3D identity matrix is:
Any 3D linear transformation can be represented by a matrix in which the three columns are the images of the points , and , respectively.
For example, if under a linear transformation the point
then the matrix representing this transformation is:
The determinant of a 3D matrix representing a linear transformation is the scale factor of the change in volume of the original shape.
Example: Find the volume of the image of a cube of volume after being transformed by the matrix:
Using the calculator to do the determinant calculation for volume in 3D:
=
The volume of the new shape is , and the orientation has changed (since the determinant is negative).
When reflecting in 3D, we reflect in a plane rather than a line:
Reflection matrices transform vectors by flipping their coordinates relative to a given plane. The unaffected coordinates remain the same, while the reflected coordinate changes sign.
Here, only the s change, while the and coordinates remain unchanged.
For example:
The reflection matrix for this transformation is:
Here, only the changes sign.
Only the changes sign.
Example: Reflect the vector
in the plane.
Step 1**:** Use the reflection matrix :
Step 2**:** Multiply the matrix by the vector :
Step 3**:** Perform the matrix-vector multiplication:
The reflected vector is
Rotation matrices describe transformations where a vector is rotated about a specific axis by an angle .
Example: Rotate the vector
by about the .
Step 1: Use the rotation matrix for rotation. For :
Step 2: Multiply by the vector :
Step 3: Perform the matrix-vector multiplication:
The rotated vector is
which shows a counterclockwise rotation about the
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