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How is a matrix a function that takes a vector to a vector, and what do composition and inverse mean for it?

Topic 4.13 Matrices as Functions: interpret a matrix as a function from vectors to vectors, and relate matrix multiplication to composition and the inverse matrix to the inverse function.

A focused answer to AP Precalculus Topic 4.13, covering how a matrix is a function from input vectors to output vectors, how matrix multiplication corresponds to composing these functions, and how the inverse matrix undoes the transformation.

Generated by Claude Opus 4.89 min answer

Reviewed by: AI editorial process; not yet individually human-reviewed

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  1. What this topic is asking
  2. A matrix as a function on vectors
  3. Multiplication is composition
  4. The identity and the inverse
  5. Why this view unifies the unit
  6. Try this

What this topic is asking

The College Board (Topic 4.13) wants you to view a matrix as a function whose input is a vector and whose output is a vector. In this view, matrix multiplication is composition of functions, the identity matrix is the do-nothing function, and the inverse matrix is the inverse function that undoes the transformation.

A matrix as a function on vectors

So the domain and range are sets of vectors, and the matrix is the rule, exactly the function structure of Unit 2 with vectors in place of numbers.

Multiplication is composition

Composition of matrix functions is the geometric "do one transformation then another", and it is computed by multiplying the matrices in the right order.

The identity and the inverse

Why this view unifies the unit

A point worth stating once is that the function lens turns every matrix fact into a familiar function fact. Multiplication is composition (Topic 2.7), the identity matrix is f(x)=xf(x) = x, the inverse matrix is f1f^{-1} (Topic 2.8), and the invertibility condition detA0\det A \ne 0 is the matrix form of one-to-one. Even non-commutativity becomes intuitive: composing functions in a different order generally gives a different function. Reading matrices as functions on vectors lets you transfer all the reasoning you built in Unit 2 to the geometry of the plane, which is the conceptual payoff of the whole matrix sequence and the basis for the modelling applications of Topic 4.14.

Try this

Q1. What does the identity matrix do to a vector? [1 point]

  • Cue. Nothing: Iv=vI\mathbf{v} = \mathbf{v}, leaving the vector unchanged.

Q2. If "apply BB first, then AA" is wanted, which product do you compute? [1 point]

  • Cue. ABAB: the rightmost matrix acts first, so BB on the right.

Exam-style practice questions

Practice questions written in the style of College Board exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.

AP 2025 (style)1 marksSection I, Part A (multiple choice, no calculator). A matrix AA is viewed as a function on vectors. Applying AA then A1A^{-1} to a vector v\mathbf{v} gives which result? (A) 0\mathbf{0} (B) v\mathbf{v} (C) 2v2\mathbf{v} (D) AvA\mathbf{v}
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The correct answer is (B), v\mathbf{v}.

The inverse matrix undoes the original transformation, so A1(Av)=(A1A)v=Iv=vA^{-1}(A\mathbf{v}) = (A^{-1}A)\mathbf{v} = I\mathbf{v} = \mathbf{v}. Composing a function with its inverse returns the input unchanged, exactly as for ordinary inverse functions.

AP 2025 (style)4 marksSection II (free response, no calculator). Let A=[0110]A = \begin{bmatrix} 0 & -1 \\ 1 & 0 \end{bmatrix} (a 9090^\circ rotation) and B=[1001]B = \begin{bmatrix} 1 & 0 \\ 0 & -1 \end{bmatrix} (a reflection over the xx-axis), viewed as functions on vectors. (a) Find the matrix that applies AA first, then BB. (b) Apply it to [10]\begin{bmatrix} 1 \\ 0 \end{bmatrix}.
Show worked answer →

A 4-point question on composing matrix functions.

(a) Composition (2 points): "apply AA first, then BB" is the product BABA (rightmost acts first): BA=[1001][0110]=[0110]BA = \begin{bmatrix} 1 & 0 \\ 0 & -1 \end{bmatrix}\begin{bmatrix} 0 & -1 \\ 1 & 0 \end{bmatrix} = \begin{bmatrix} 0 & -1 \\ -1 & 0 \end{bmatrix}.
(b) Apply (2 points): [0110][10]=[01]\begin{bmatrix} 0 & -1 \\ -1 & 0 \end{bmatrix}\begin{bmatrix} 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 0 \\ -1 \end{bmatrix}. The vector is rotated to point up, then reflected to point down.

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