Proof Use the properties of matrix multiplication to prove the first three properties of Theorem
Theorem 5.3 Properties of the Dot Product
If
1.
2.
3.
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- 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_forwardGuided Proof Prove that if u is orthogonal to v and w, then u is orthogonal to cv+dw for any scalars c and d. Getting Started: To prove that u is orthogonal to cv+dw, you need to show that the dot product of u and cv+dw is 0. i Rewrite the dot product of u and cv+dw as a linear combination of (uv) and (uw) using Properties 2 and 3 of Theorem 5.3. ii Use the fact that u is orthogonal to v and w, and the result of part i, to lead to the conclusion that u is orthogonal to cv+dw.arrow_forwardProof Complete the proof of the cancellation property of vector addition by justifying each step. Prove that if u, v, and w are vectors in a vector space V such that u+w=v+w, then u=v. u+w=v+wu+w+(w)=v+w+(w)a._u+(w+(w))=v+(w+(w))b._u+0=v+0c._ u=vd.arrow_forward
- Illustrate 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_forwardProof Let A be an nn square matrix. Prove that the row vectors of A are linearly dependent if and only if the column vectors of A are linearly dependent.arrow_forwardCAPSTONE (a) Explain how to determine whether a function defines an inner product. (b) Let u and v be vectors in an inner product space V, such that v0. Explain how to find the orthogonal projection of u onto v.arrow_forward
- Proof Prove that each statement is true when A and B are square matrices of order n and c is a scalar. a TrA+B=TrA+TrB b TrcA=cTrAarrow_forwardTrue or False? In Exercises 57and 58, determine whether each statement is true or false. If a statement is true, give a reason or cite an appropriate statement from text. If a statement is false, provide an example that shows the statement is not true in all cases or cite an appropriate statement from the text. (a) To subtract two vectors in Rn, subtract their corresponding components. (b) The zero vector 0 in Rn is the additive inverse of a vector.arrow_forwardTrue or false? det(A) is defined only for a square matrix A.arrow_forward
- True or false?In Exercises 85 and 86, determine whether each statement is true or false. If a statement is true, give a reason or cite an appropriate statement from the text. If a statement is false, provide an example that shows the statement is not true in all cases or cite an appropriate statement from the text. a The dot product is the only inner product that can be defined in Rn. b A nonzero vector in an inner product can have a norm of zero.arrow_forwardVector Operations In Exercises 19-24, let u=(1,2,3), v=(2,2,-1), and w=(4,0,-4). Find u-v and v-u.arrow_forwardGuided Proof Prove that if w is orthogonal to each vector in S={v1,v2,,vn}, then w is orthogonal to every linear combination of vector in S. Getting Started: To prove that w is orthogonal to every linear combination of vectors in S, you need to show that their inner product is 0. i Write v as a linear combination of vectors, with arbitrary scalars c1,,cn in S. ii Form the inner product of w and v. iii Use the properties of inner products to rewrite the inner product w,v as a linear combination of the inner products w,vi, i=1,,n. iv Use the fact that w is orthogonal to each vector in S to lead to the conclusion that w is orthogonal to v.arrow_forward
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