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In Exercises 11 and 12, \(B\) and \(C\) are bases for a vector space \(V\) . Mark each statement True or False. Justify each answer.

a. The columns of \(\mathop P\limits_{C \to B} \) are linearly independent.

b. If \(V = {\mathbb{R}^2}\), \(B = \left\{ {{b_1},{b_2}} \right\}\),\(C = \left\{ {{c_1},{c_2}} \right\}\) then row reduction of \(\left( {{c_1}\,\,\,\,{c_2}\,\,\,{b_1}\,\,\,{b_2}} \right)\)to \(\left( {I\,\,\,\,\,P} \right)\)produces a matrix \(P\) that satisfies \({\left( x \right)_B} = P{\left( x \right)_C}\) for all \(x\) in \(V\).

Short Answer

Expert verified

(a) True

The columns of matrix \(\mathop P\limits_{C \to B} \) are always linearly independent, which are also the vectors in basis \(B\).

(b) False

The reduction of\(\left( {{c_1}\,\,\,\,{c_2}\,\,\,{b_1}\,\,\,{b_2}} \right)\)to\(\left( {I\,\,\,\,\,P} \right)\)produces matrix\(P\)that satisfies\({\left( x \right)_C} = P{\left( x \right)_B}\)for all\(x\)in\(V\).

Step by step solution

01

Assume \(B\) and \(C\) as the bases for vector space \(V\)and \(\xi \) as the standard basis in \({\mathbb{R}^n}\)

Assume \(B = \left\{ {{b_1}.....{b_n}} \right\}\) and \(C = \left\{ {{c_1}.....{c_n}} \right\}\) are the bases for vector space \(V\) and \(\xi = \left\{ {{e_1}......{e_n}} \right\}\) is the standard basis in \({\mathbb{R}^n}\).

02

Use the theorem for change of coordinates matrix from \(B\) to \(C\) and the concept of row reduction

If \(B = \left\{ {{b_1}.....{b_n}} \right\}\) and \(C = \left\{ {{c_1}.....{c_n}} \right\}\) are the bases for vector space \(V\), then according to the theorem of change of coordinates matrix from \(B\) to \(C\), the vectors in basis \(B\) have \(C\) coordinate vector, which are the same as the columns of \(\mathop P\limits_{C \to B} \). Thus, these columns are linearly independent.

If \(B = \left\{ {{b_1}.....{b_n}} \right\}\) and \(C = \left\{ {{c_1}.....{c_n}} \right\}\) are the bases in \(V = {\mathbb{R}^2}\), then according to the concept of row reduction, the reduction of\(\left( {{c_1}\,\,\,\,{c_2}\,\,\,{b_1}\,\,\,{b_2}} \right)\)to\(\left( {I\,\,\,\,\,P} \right)\)produces matrix\(P\)that satisfies\({\left( x \right)_C} = P{\left( x \right)_B}\)for all\(x\)in\(V\).

03

Draw a conclusion

So, statement (a) is true, and statement (b) is false.

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Most popular questions from this chapter

Let be a basis of\({\mathbb{R}^n}\). .Produce a description of an \(B = \left\{ {{{\bf{b}}_{\bf{1}}},....,{{\bf{b}}_n}\,} \right\}\)matrix A that implements the coordinate mapping \({\bf{x}} \mapsto {\left( {\bf{x}} \right)_B}\). Find it. (Hint: Multiplication by A should transform a vector x into its coordinate vector \({\left( {\bf{x}} \right)_B}\)). (See Exercise 21.)

Let \(V\) and \(W\) be vector spaces, and let \(T:V \to W\) be a linear transformation. Given a subspace \(U\) of \(V\), let \(T\left( U \right)\) denote the set of all images of the form \(T\left( {\mathop{\rm x}\nolimits} \right)\), where x is in \(U\). Show that \(T\left( U \right)\) is a subspace of \(W\).

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

13. Show that if \(P\) is an invertible \(m \times m\) matrix, then rank\(PA\)=rank\(A\).(Hint: Apply Exercise12 to \(PA\) and \({P^{ - 1}}\left( {PA} \right)\).)

Use coordinate vector to test whether the following sets of poynomial span \({{\bf{P}}_{\bf{2}}}\). Justify your conclusions.

a. \({\bf{1}} - {\bf{3}}t + {\bf{5}}{t^{\bf{2}}}\), \( - {\bf{3}} + {\bf{5}}t - {\bf{7}}{t^{\bf{2}}}\), \( - {\bf{4}} + {\bf{5}}t - {\bf{6}}{t^{\bf{2}}}\), \({\bf{1}} - {t^{\bf{2}}}\)

b. \({\bf{5}}t + {t^{\bf{2}}}\), \({\bf{1}} - {\bf{8}}t - {\bf{2}}{t^{\bf{2}}}\), \( - {\bf{3}} + {\bf{4}}t + {\bf{2}}{t^{\bf{2}}}\), \({\bf{2}} - {\bf{3}}t\)

Consider the polynomials , and \({p_{\bf{3}}}\left( t \right) = {\bf{2}}\) \({p_{\bf{1}}}\left( t \right) = {\bf{1}} + t,{p_{\bf{2}}}\left( t \right) = {\bf{1}} - t\)(for all t). By inspection, write a linear dependence relation among \({p_{\bf{1}}},{p_{\bf{2}}},\) and \({p_{\bf{3}}}\). Then find a basis for Span\(\left\{ {{p_{\bf{1}}},{p_{\bf{2}}},{p_{\bf{3}}}} \right\}\).

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