# How is a vector space defined without a basis

The title pretty much says it all; is a vector space meaningless without a choice of basis which has been predefined? I've been reading through my algebra book and it says something like, take a vector $$v$$ and let $$x$$ be its coordinate with respect to a particular basis. My question is, how can you even take a vector before you assign a basis to its vector space? I know similar questions may have been asked here, but they all involve something about the Axiom of Completeness, which I have not learned about yet. Thanks so much for your help!

• For example, the set $V$ of all $m \times n$ matrices $A$ such that $\text{trace}(A) = 0$ is a vector space. We have not yet specified a basis for $V$. – littleO Aug 14 at 0:22
• Linear algebra is largely a collection of conceptual rules that relate abstractly defined subspaces of vector spaces. Like the image of the adjoint of a linear map is the annihilator of its kernel. The examples often rely on bases, and the means of proof are very concrete, but the content is abstract. – Charlie Frohman Aug 14 at 0:26
• Indeed, in an infinite-dimensional vector space, in general you can't write down an explicit basis at all, as the existence of a basis depends on the axiom of choice. – Bungo Aug 14 at 0:35
• @Bungo Whoa, I didn't know that! I guess even in math everything is somewhat relative? – DavidNiu Aug 14 at 0:37
• "even in math everything is somewhat relative" I don't know what that means. But I like the enthusiasm. – littleO Aug 14 at 0:44

Any set of objects that satisfies the relevant axioms is a vector space. Not all vectors are tuples of scalars, although that’s certainly what you work with most in introductory courses. For instance, the set of real-valued functions defined on the interval $$[0,1]$$ forms a vector space over the reals. I’d be hard-pressed to even define a basis for this space at all.
Now, for a finite-dimensional space over some field $$\mathbb K$$, choosing a basis amounts to defining an isomorphism between the space and $$\mathbb K^n$$, which is why you can focus on tuples of scalars when studying finite-dimensional vector spaces.