If the basis of a vector space is known, then every vector (element of the vector space) can be expressed as a linear combination of the basis vectors.

This is to be expected, since the basis of a vector space contains only linearly independent vectors, so any non-basis vectors must be linearly dependent, and hence able to be expressed using a linear combination.

So far, it hasn’t been properly mentioned, but almost all references to bases refer to ordered bases, where elements of the bases have a certain order and can’t be rearranged once that order is defined.

Expressing vectors from a basis uniquely ^theorem

If is the ordered basis of a vector space (fixed over the field ) then every vector in can be expressed uniquely, as a linear combination of the basis, i.e.:


This is usually done by solving a linear system consisting of the basis vectors.

Now that we know every vector can be expressed, we can connect vector spaces to a coordinate system (such as that of the Cartesian Plane ()), using coordinate vectors

Coordinate Vectors

Coordinates relative to a Basis

If is the ordered basis of a vector space (fixed over the field ) then every vector in can be expressed uniquely as:


The set of unique scalars, are the coordinates of relative to . Then:

is the coordinate vector of with respect to

The existence of these coordinate vectors means that a vector in can be uniquely represented by any basis of .

Furthermore, these coordinate vectors are always linked, even during a linear combination:

Coordinate Vectors are Vectors

Let be a vector space fixed with the field . Also, let be the ordered basis of . If and :