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Each statement in Exercises 33-38 is either true (in all cases) or false (for at least one example). If false, construct a specific example to show that the statement is not always true. Such an example is called a counterexample to the statement. If a statement is true, give a justification. (One specific example cannot explain why a statement is always true. You will have to do more work here than in Exercises 21 and 22.)

35. If \({{\mathop{\rm v}\nolimits} _1}\) and \({v_2}\) are in \({\mathbb{R}^4}\) and \({{\mathop{\rm v}\nolimits} _2}\) is not a scalar multiple of \({v_1}\), then \(\left\{ {{v_1},{v_2}} \right\}\) is linearly independent.

Short Answer

Expert verified

The given statement is false.

Step by step solution

01

Determine whether the given statement is true or false

If set \(S = \left\{ {{{\mathop{\rm v}\nolimits} _1},...,{v_p}} \right\}\) in \({\mathbb{R}^n}\) contains the zero vector, then it islinearly dependent.

If the vector is a zero vector, then it is not linearly independent.

Thus, the given statement is false.

02

Construct an example to show that the statement is not always true

Take \({{\mathop{\rm v}\nolimits} _1}\) to be not a scalar multiple of vector \({{\mathop{\rm v}\nolimits} _2}\).

\({{\mathop{\rm v}\nolimits} _1} = \left[ {\begin{array}{*{20}{c}}0\\0\\0\\0\end{array}} \right]\), \({{\mathop{\rm v}\nolimits} _2} = \left[ {\begin{array}{*{20}{c}}1\\1\\1\\1\end{array}} \right]\)

Since the vector in \({\mathbb{R}^4}\) contains the zero vector, the set is not linearly independent.

Thus, the given statement is false.

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Most popular questions from this chapter

Find an equation involving \(g,\,h,\)and \(k\) that makes this augmented matrix correspond to a consistent system:

\(\left[ {\begin{array}{*{20}{c}}1&{ - 4}&7&g\\0&3&{ - 5}&h\\{ - 2}&5&{ - 9}&k\end{array}} \right]\)

Suppose a linear transformation \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) has the property that \(T\left( {\mathop{\rm u}\nolimits} \right) = T\left( {\mathop{\rm v}\nolimits} \right)\) for some pair of distinct vectors u and v in \({\mathbb{R}^n}\). Can Tmap \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\)? Why or why not?

Suppose Tand Ssatisfy the invertibility equations (1) and (2), where T is a linear transformation. Show directly that Sis a linear transformation. (Hint: Given u, v in \({\mathbb{R}^n}\), let \({\mathop{\rm x}\nolimits} = S\left( {\mathop{\rm u}\nolimits} \right),{\mathop{\rm y}\nolimits} = S\left( {\mathop{\rm v}\nolimits} \right)\). Then \(T\left( {\mathop{\rm x}\nolimits} \right) = {\mathop{\rm u}\nolimits} \), \(T\left( {\mathop{\rm y}\nolimits} \right) = {\mathop{\rm v}\nolimits} \). Why? Apply Sto both sides of the equation \(T\left( {\mathop{\rm x}\nolimits} \right) + T\left( {\mathop{\rm y}\nolimits} \right) = T\left( {{\mathop{\rm x}\nolimits} + y} \right)\). Also, consider \(T\left( {cx} \right) = cT\left( x \right)\).)

Determine which of the matrices in Exercises 7–12areorthogonal. If orthogonal, find the inverse.

11. \(\left( {\begin{aligned}{{}}{2/3}&{2/3}&{1/3}\\0&{1/3}&{ - 2/3}\\{5/3}&{ - 4/3}&{ - 2/3}\end{aligned}} \right)\)

Suppose Ais an \(n \times n\) matrix with the property that the equation \(Ax = 0\)has only the trivial solution. Without using the Invertible Matrix Theorem, explain directly why the equation \(Ax = b\) must have a solution for each b in \({\mathbb{R}^n}\).

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