5. Let V be a vector space (note that this is an arbitrary vector space - not necessarily F"). Suppose dim(V) = n. Prove that a set of vectors {v₁,..., Vn} in V is linearly independent if and only if it spans V. Hint 1: Remember (from sec. 1.6) that there is always an isomorphism A: V → F and isomorphisms "preserve" bases (and so preserves linear independence). Hint 2: Think in terms of pivots.

Find an orthonormal basis for the subspace of Euclidean 3 space below. W={(x1,x2,x3):x1+x2+x3=0}

Let 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.

Take this test to review the material in Chapters 4 and 5. After you are finished, check your work against the answers in the back of the book. Prove that the set of all singular 33 matrices is not a vector space.

Consider the vectors u=(6,2,4) and v=(1,2,0) from Example 10. Without using Theorem 5.9, show that among all the scalar multiples cv of the vector v, the projection of u onto v is the closest to u that is, show that d(u,projvu) is a minimum.

Find the kernel of the linear transformation T:R4R4, T(x1,x2,x3,x4)=(x1x2,x2x1,0,x3+x4).

Let V be an two dimensional subspace of R4 spanned by (0,1,0,1) and (0,2,0,0). Write the vector u=(1,1,1,1) in the form u=v+w, where v is in V and w is orthogonal to every vector in V.

Let T be a linear transformation T such that T(v)=kv for v in Rn. Find the standard matrix for T.

Prove that if A is similar to B and A is diagonalizable, then B is diagonalizable.

Let V be the set of all positive real numbers. Determine whether V is a vector space with the operations shown below. x+y=xyAddition cx=xcScalar multiplication If it is, verify each vector space axiom; if it is not, state all vector space axioms that fail.