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  1. AP Pre Calculus
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Glossary

L

Linear Transformation

Criticality: 3

A special type of function that takes an input vector and produces an output vector, while preserving vector addition and scalar multiplication.

Example:

Rotating a shape on a coordinate plane is a linear transformation because it maintains the relative positions and scaling of its vertices.

M

Matrices

Criticality: 3

Rectangular arrays of numbers, symbols, or expressions arranged in rows and columns, commonly used to represent linear transformations or collections of vectors.

Example:

A 2x2 matrix can represent a transformation that scales an image, making it twice as large.

Matrix Multiplication

Criticality: 3

A binary operation that combines two matrices to produce a new matrix, where the entries of the result are calculated from the dot product of rows and columns of the input matrices.

Example:

To apply a rotation followed by a scaling to a set of points, you would perform matrix multiplication of the rotation matrix and the scaling matrix.

P

Preserves Addition

Criticality: 2

A property of linear transformations where the transformation of a sum of vectors is equal to the sum of the transformations of individual vectors (T(u + v) = T(u) + T(v)).

Example:

If you transform two separate forces acting on an object and then add them, the result is the same as adding the forces first and then transforming their sum; this shows the transformation preserves addition.

Preserves Scalar Multiplication

Criticality: 2

A property of linear transformations where the transformation of a scalar multiple of a vector is equal to the scalar multiple of the transformed vector (T(cu) = cT(u)).

Example:

If you double the velocity vector of a car and then apply a linear transformation, it's equivalent to applying the transformation first and then doubling the transformed velocity vector, demonstrating it preserves scalar multiplication.

S

Set of n Vectors in R²

Criticality: 2

Multiple vectors in a two-dimensional space, represented as a 2xn matrix where each column corresponds to an individual vector.

Example:

To track the movement of five different drones simultaneously, you could organize their current positions as a set of n vectors in R² in a 2x5 matrix.

Single Vector in R² (Column Vector)

Criticality: 2

A vector in a two-dimensional space (R²) typically represented as a 2x1 matrix, or a column with two components (x, y).

Example:

The coordinates of a treasure chest at (5, -3) on a map can be written as a single vector in R², [5; -3].

T

Transformation Matrix

Criticality: 3

A specific matrix that uniquely represents a linear transformation, allowing the transformation to be applied to a vector by left-multiplying the vector by this matrix.

Example:

To reflect a point across the y-axis, you would use a specific transformation matrix [[-1, 0], [0, 1]].

Z

Zero Vector (Null Vector)

Criticality: 2

A vector in which all components are zero, representing the origin in a vector space; linear transformations always map this vector to itself.

Example:

In a game, if a character is at the origin (0,0), its position is represented by the zero vector.