Orthogonal and Orthonormal Sets In Exercises 1-12, (a) determine whether the set of
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Elementary Linear Algebra (MindTap Course List)
- Proof Prove that if S={v1,v2,,vn} is a basis for a vector space V and c is a nonzero scalar, then the set S1={cv1,cv2,,cvn} is also a basis for V.arrow_forwardProofProve in full detail that M2,2, with the standard operations, is a vector space.arrow_forwardLet v1, v2, and v3 be three linearly independent vectors in a vector space V. Is the set {v12v2,2v23v3,3v3v1} linearly dependent or linearly independent? Explain.arrow_forward
- Proof In Exercises 6568, complete the proof of the remaining properties of theorem 4.3 by supplying the justification for each step. Use the properties of vector addition and scalar multiplication from theorem 4.2. Property 6: (v)=v (v)+(v)=0andv+(v)=0a.(v)+(v)=v+(v)b.(v)+(v)+v=v+(v)+vc.(v)+((v)+v)=v+((v)+v)d. (v)+0=v+0e.(v)=vf.arrow_forwardProof When V is spanned by {v1,v2,...,vk} and one of these vector can be written as a linear combination of the other k1 vectors, prove that the span of these k1 vector is also V.arrow_forwardExplaining Why a Set Is Not a BasisIn Exercises 23-30, explain why S is not a basis for P2. S={1,2x,4+x2,5x}arrow_forward
- Proof Prove Theorem 4.12. THEOREM 4.12 Basis Tests in an n-Dimensional Space Let V be a vector space of dimension n. 1. If S={v1,v2,,vn} is a linearly independent set of vectors in V, then S is a basis for V. 2. If S={v1,v2,,vn} spans V, then S is a basis for V.arrow_forwardLet u, v, and w be any three vectors from a vector space V. Determine whether the set of vectors {vu,wv,uw} is linearly independent or linearly dependent.arrow_forwardIllustrate properties 110 of Theorem 4.2 for u=(2,1,3,6), v=(1,4,0,1), w=(3,0,2,0), c=5, and d=2. THEOREM 4.2Properties of Vector Addition and Scalar Multiplication in Rn. Let u,v, and w be vectors in Rn, and let c and d be scalars. 1. u+v is vector in Rn. Closure under addition 2. u+v=v+u Commutative property of addition 3. (u+v)+w=u+(v+w) Associative property of addition 4. u+0=u Additive identity property 5. u+(u)=0 Additive inverse property 6. cu is a vector in Rn. Closure under scalar multiplication 7. c(u+v)=cu+cv Distributive property 8. (c+d)u=cu+du Distributive property 9. c(du)=(cd)u Associative property of multiplication 10. 1(u)=u Multiplicative identity propertyarrow_forward
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