Rotation and Reflection Matrices
Matrices that rotate or reflect the plane.
Key idea
Matrices that rotate or reflect the plane.
In depth
Rotation by θ: [cos θ −sin θ; sin θ cos θ]. Reflection across the x-axis: [1 0; 0 −1]. Both are orthogonal; rotations have determinant 1 and reflections −1.
Worked example
Rotating (1, 0) by 90° with [0 −1; 1 0] gives (0, 1).
Formula
Real-world uses
- Turning sprites in games and flipping images in photo editing software
Common mistake
Using the wrong sign for the sine terms, which rotates the other way.
How to learn this
- Read the key idea and say it in your own words.
- Work through the worked example, then try a similar problem.
- Use the interactive lesson’s visual and mini-quiz to check the pattern.
Frequently asked questions
What is Rotation and Reflection Matrices?
Matrices that rotate or reflect the plane. It is a topic at the advanced level in Linear Algebra.
What is the formula for Rotation and Reflection Matrices?
The key formula is R(θ) = [[cosθ,−sinθ],[sinθ,cosθ]].
Where is Rotation and Reflection Matrices used in real life?
Real-world examples: Turning sprites in games and flipping images in photo editing software.
What should I learn before Rotation and Reflection Matrices?
Make sure you are comfortable with Matrix of a Transformation, the previous topic in Linear Algebra.
What is a common mistake with Rotation and Reflection Matrices?
Using the wrong sign for the sine terms, which rotates the other way.
How can I practise Rotation and Reflection Matrices?
Open the interactive lesson, play with the visual, then answer the three-question mini-quiz. Getting two right marks the topic complete.
What comes after Rotation and Reflection Matrices?
Move on to Scaling and Shear Matrices next.
Related advanced topics in Linear Algebra
- Dot Product – Sum of component products.
- Angle Between Vectors – Cosine from the dot product.
- Orthogonality – Vectors are orthogonal when their dot product is 0.
- Projection – Component of one vector along another.
- Cross Product – A vector perpendicular to two vectors in 3D.
- Lines and Planes in Vector Form – Parametric and normal equations.