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Determine which pairs of vectors in Exercises \(15 - 18\) are orthogonal.

18. \(y = \left( {\begin{aligned}{ - 3}\\7\\4\\0\end{aligned}} \right),\,\,z = \left( {\begin{aligned}{1}\\{ - 8}\\{15}\\{ - 7}\end{aligned}} \right)\)

Short Answer

Expert verified

The vectors \({\bf{y}}{\rm{ and }}{\bf{z}}\) are not orthogonal to each other.

Step by step solution

01

Definition of orthogonal vectors

The two vectors \({\bf{u}}{\rm{ and }}{\bf{v}}\) are Orthogonal if \({\bf{u}} \cdot {\bf{v}} = 0\).

02

Checking Orthogonality for given vectors.

The given vectors are:

\({\bf{y}} = \left( {\begin{aligned}{*{20}{r}}{ - 3}\\7\\4\\0\end{aligned}} \right),\,\,{\bf{z}} = \left( {\begin{aligned}{*{20}{r}}1\\{ - 8}\\{15}\\{ - 7}\end{aligned}} \right)\)

On having dot products, we get:

\(\begin{aligned}{c}{\bf{y}} \cdot {\bf{z}} = \left( {\begin{aligned}{*{20}{r}}{ - 3}\\7\\4\\0\end{aligned}} \right) \cdot \left( {\begin{aligned}{*{20}{r}}1\\{ - 8}\\{15}\\{ - 7}\end{aligned}} \right)\\ = \left( { - 3} \right)\left( 1 \right) + \left( 7 \right)\left( { - 8} \right) + \left( 4 \right)\left( {15} \right) + \left( 0 \right)\left( { - 7} \right)\\ = - 3 - 56 + 60 + 0\\ = 1\end{aligned}\)

Since \({\bf{y}} \cdot {\bf{z}} \ne 0\).

Hence, the vectors \(y{\rm{ and }}z\) are not orthogonal to each other.

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Most popular questions from this chapter

a. Rewrite the data in Example 1 with new \(x\)-coordinates in mean deviation form. Let \(X\) be the associated design matrix. Why are the columns of \(X\) orthogonal?

b. Write the normal equations for the data in part (a), and solve them to find the least-squares line, \(y = {\beta _0} + {\beta _1}x*\), where \(x* = x - 5.5\).

In Exercises 5 and 6, describe all least squares solutions of the equation \(A{\bf{x}} = {\bf{b}}\).

6.\(A = \left( {\begin{aligned}{{}{}}{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{1}}&{\bf{0}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\\{\bf{1}}&{\bf{0}}&{\bf{1}}\end{aligned}} \right)\),\({\bf{b}} = \left( {\begin{aligned}{{}{}}{\bf{7}}\\{\bf{2}}\\{\bf{3}}\\{\bf{6}}\\{\bf{5}}\\{\bf{4}}\end{aligned}} \right)\)

Let \(\left\{ {{{\bf{v}}_1}, \ldots ,{{\bf{v}}_p}} \right\}\) be an orthonormal set in \({\mathbb{R}^n}\). Verify the following inequality, called Bessel’s inequality, which is true for each x in \({\mathbb{R}^n}\):

\({\left\| {\bf{x}} \right\|^2} \ge {\left| {{\bf{x}} \cdot {{\bf{v}}_1}} \right|^2} + {\left| {{\bf{x}} \cdot {{\bf{v}}_2}} \right|^2} + \ldots + {\left| {{\bf{x}} \cdot {{\bf{v}}_p}} \right|^2}\)

Compute the least-squares error associated with the least square solution found in Exercise 4.

In Exercises 7–10, let\[W\]be the subspace spanned by the\[{\bf{u}}\]’s, and write y as the sum of a vector in\[W\]and a vector orthogonal to\[W\].

8.\[y = \left[ {\begin{aligned}{ - 1}\\4\\3\end{aligned}} \right]\],\[{{\bf{u}}_1} = \left[ {\begin{aligned}1\\1\\{\bf{1}}\end{aligned}} \right]\],\[{{\bf{u}}_2} = \left[ {\begin{aligned}{ - 1}\\3\\{ - 2}\end{aligned}} \right]\]

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