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The dot product

Evaluating dot products, finding the cosine of the angle between vectors, and verifying the Cauchy-Schwarz inequality with its equality condition.

Matrix Theory and Linear Algebra, The dot product

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13 exercises

Exercise 2.6.1

Find [1234]⋅[2013]\left[\begin{array}{r}1\\ 2\\ 3\\ 4\end{array}\right]\boldsymbol{\cdot}\left[\begin{array}{r}2\\ 0\\ 1\\ 3\end{array}\right].

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Exercise 2.6.4

Find cos⁡θ\cos\theta where θ\theta is the angle between the vectors

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Exercise 2.6.5

Find cos⁡θ\cos\theta where θ\theta is the angle between the vectors

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Exercise 2.6.6

Use the formula given in Proposition 2.47 to verify the Cauchy Schwarz inequality and to show that equality occurs if and only if one of the vectors is a scalar multiple of the other.

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Exercise 2.6.7

Show that the triangle with vertices A=(2,0,−3)A=(2,0,-3), B=(5,−2,1)B=(5,-2,1) and C=(7,5,3)C=(7,5,3) is a right triangle.

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Exercise 2.6.8

Find proj⁡v(w)\operatorname{proj}_{\mathbf{v}}(\mathbf{w}) where w=[10−2]\mathbf{w}=\left[\begin{array}{r}1\\ 0\\ -2\end{array}\right] and v=[123]\mathbf{v}=\left[\begin{array}{r}1\\ 2\\ 3\end{array}\right].

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Exercise 2.6.9

Find proj⁡v(w)\operatorname{proj}_{\mathbf{v}}(\mathbf{w}) where w=[12−2]\mathbf{w}=\left[\begin{array}{r}1\\ 2\\ -2\end{array}\right] and v=[103]\mathbf{v}=\left[\begin{array}{r}1\\ 0\\ 3\end{array}\right].

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Exercise 2.6.10

Find proj⁡v(w)\operatorname{proj}_{\mathbf{v}}(\mathbf{w}) where w=[12−21]\mathbf{w}=\left[\begin{array}{r}1\\ 2\\ -2\\ 1\end{array}\right] and v=[1230]\mathbf{v}=\left[\begin{array}{r}1\\ 2\\ 3\\ 0\end{array}\right].

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Exercise 2.6.13

Does it make sense to speak of proj⁡0(w)\operatorname{proj}_{\mathbf{0}}(\mathbf{w})?

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Exercise 2.6.14

Decompose the vector v\mathbf{v} into v=a+b\mathbf{v}=\mathbf{a}+\mathbf{b} where a\mathbf{a} is parallel to u\mathbf{u} and b\mathbf{b} is orthogonal to u\mathbf{u}.

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Exercise 2.6.15

Prove the Cauchy Schwarz inequality in Rn\mathbb{R}^{n} as follows. For u,v\mathbf{u},\mathbf{v} vectors, consider

Simplify using the axioms of the dot product and then put in the formula for the projection. Notice that this expression equals 00 and you get equality in the Cauchy Schwarz inequality if and only if u=proj⁡v(u)\mathbf{u}=\operatorname{proj}_{\mathbf{v}}(\mathbf{u}). What is the geometric meaning of u=proj⁡v(u)\mathbf{u}=\operatorname{proj}_{\mathbf{v}}(\mathbf{u})?

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Exercise 2.6.16

Let v,w\mathbf{v},\mathbf{w} u\mathbf{u} be vectors. Show that (w+u)⊥=w⊥+u⊥(\mathbf{w}+\mathbf{u})_{\perp}=\mathbf{w}_{\perp}+\mathbf{u}_{\perp}, where w⊥=w−proj⁡v(w)\mathbf{w}_{\perp}=\mathbf{w}-\operatorname{proj}_{\mathbf{v}}(\mathbf{w}).

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Exercise 2.6.17

Show that

and conclude every vector in Rn\mathbb{R}^{n} can be written as the sum of two vectors, one which is orthogonal and one which is parallel to the given vector.

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Adapted from Matrix Theory and Linear Algebra © 2017–2026 Peter Selinger, Lyryx Learning, and Ken Kuttler. Licensed under CC BY 4.0. Source: Matrix Theory and Linear Algebra. Imported at revision d74bc3a.