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In exercises 1-6, determine which sets of vectors are orthogonal.

\(\left[ {\begin{align} 2\\{-5}\\{-3}\end{align}} \right]\), \(\left[ {\begin{align}0\\0\\0\end{align}} \right]\), \(\left[ {\begin{align} 4\\{ - 2}\\6\end{align}} \right]\)

Short Answer

Expert verified

The given set is orthogonal.

Step by step solution

01

Definition of an orthogonal set

If \[{{\bf{u}}_i} \cdot {{\bf{u}}_j} = 0\] for \[i \ne j\], then the set of vectors \[\left\{ {{{\bf{u}}_1}, \ldots ,{{\bf{u}}_p}} \right\} \in {\mathbb{R}^n}\] is said to be orthogonal.

02

Check for orthogonality of vectors

Let the given vectors be, \({u_1} = \left[ {\begin{align}2\\{-5}\\{-3}\end{align}} \right]\), \({u_2} = \left[ {\begin{align}0\\0\\0\end{align}} \right]\) and \({u_3} = \left[ {\begin{align}4\\{ - 2}\\6\end{align}} \right]\).

First, find \({u_1} \cdot {u_2}\):

\(\begin{align}{c}{u_1} \cdot {u_2} = \left( 2 \right)\left( 0 \right) + \left( { - 5} \right)\left( 0 \right) + \left( { - 3} \right)\left( 0 \right)\\ = 0 - 0 - 0\\ = 0\end{align}\)

Now, find \({u_2} \cdot {u_3}\):

\(\begin{align}{c}{u_2} \cdot {u_3} = \left( 0 \right)\left( 4 \right) + \left( 0 \right)\left( { - 2} \right) + \left( 0 \right)\left( 6 \right)\\ = 0 - 0 + 0\\ = 0\end{align}\)

And find \({u_1} \cdot {u_3}\):

\(\begin{align}{c}{u_1} \cdot {u_3} = \left( 2 \right)\left( 4 \right) + \left( { - 5} \right)\left( { - 2} \right) + \left( { - 3} \right)\left( 6 \right)\\ = 8 + 10 - 18\\ = 0\end{align}\)

Since all the pairs are orthogonal hence, the given set is orthogonal.

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Most popular questions from this chapter

Let \({\mathbb{R}^{\bf{2}}}\) have the inner product of Example 1. Show that the Cauchy-Schwarz inequality holds for \({\bf{x}} = \left( {{\bf{3}}, - {\bf{2}}} \right)\) and \({\bf{y}} = \left( { - {\bf{2}},{\bf{1}}} \right)\). (Suggestion: Study \({\left| {\left\langle {{\bf{x}},{\bf{y}}} \right\rangle } \right|^{\bf{2}}}\).)

To measure the take-off performance of an airplane, the horizontal position of the plane was measured every second, from \(t = 0\) to \(t = 12\). The positions (in feet) were: 0, 8.8, 29.9, 62.0, 104.7, 159.1, 222.0, 294.5, 380.4, 471.1, 571.7, 686.8, 809.2.

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In exercises 1-6, determine which sets of vectors are orthogonal.

\(\left[ {\begin{array}{*{20}{c}}3\\{-2}\\1\\3\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}{-1}\\3\\{-3}\\4\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}3\\8\\7\\0\end{array}} \right]\)

In Exercises 1-4, find the equation \(y = {\beta _0} + {\beta _1}x\) of the least-square line that best fits the given data points.

4. \(\left( {2,3} \right),\left( {3,2} \right),\left( {5,1} \right),\left( {6,0} \right)\)

In Exercises 1-4, find a least-sqaures solution of \(A{\bf{x}} = {\bf{b}}\) by (a) constructing a normal equations for \({\bf{\hat x}}\) and (b) solving for \({\bf{\hat x}}\).

1. \(A = \left[ {\begin{aligned}{{}{}}{ - {\bf{1}}}&{\bf{2}}\\{\bf{2}}&{ - {\bf{3}}}\\{ - {\bf{1}}}&{\bf{3}}\end{aligned}} \right]\), \({\bf{b}} = \left[ {\begin{aligned}{{}{}}{\bf{4}}\\{\bf{1}}\\{\bf{2}}\end{aligned}} \right]\)

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