Definition:Vector/Real Euclidean Space

Definition
A vector is defined as an element of a vector space.

We have that $\R^n$ is a vector space.

Hence a vector in $\R^n$ is defined as any element of $\R^n$.

Note that such a vector is so commonly used that sometimes the term vector is implied to mean "a vector in $\R^n$".

$\R^1$
As $\R$ forms a vector space, every real number is a vector.

Note that as $\R$ is a vector space over itself, every real number is also a scalar.

Hence a vector in $\R^n$ is sometimes imprecisely used to mean "a vector in $\R^n$, $n > 1$".

Geometric Interpretation
From Real Number Line, the real number space $\R$ is often represented by an infinite straight line.

By the same token, a vector in $\R$ can be represented by a directed line segment.

Formally, a vector $\langle{x_1}\rangle, \ x_1 \in \R$ is accurately represented by the set of all directed line segments having:


 * Magnitude $\left \vert{x_1}\right \vert$


 * Direction dependent on whether $x_1 < 0$ or $x_1 > 0$

By convention, if only one axis is under consideration, the line is placed horizontally, such that segments oriented towards the right are positive, to the left negative.

Note that in such a context the zero vector can be interpreted as a directed line segment beginning and terminating at the same point.

$\R^2$
We have that $\R^2$ is a vector space.

Hence any 2-tuple of $2$ real numbers is a vector.

Geometric Interpretation
From Real Number Plane, we can represent the vector space $\R^2$ by points on the plane.

That is, every pair of coordinates $\left({x_1,x_2}\right)$ can be uniquely defined by a point in the plane.

An arrow with base at the origin and terminal point $\left({x_1,x_2}\right)$ is defined to have the length equal to the magnitude of the vector, and direction defined by the relative location of $\left({x_1,x_2}\right)$ with the origin as the point of reference.

Each vector is then represented by the set of all directed line segments with:


 * Magnitude $\sqrt{x_1^2 + x_2^2}$


 * Direction equal to the direction of $\overrightarrow{\left({0,0}\right)\left({x_1,x_2}\right)}$

Notation
Several conventions are found in the literature for annotating a general vector in a style that distinguishes it from a scalar, as follows.

Let $\left\{{x_1, x_2, \ldots, x_n}\right\}$ be a collection of scalars which form the components of an $n$-dimensional vector.

The vector $\left({x_1, x_2, \ldots, x_n}\right)$ can be annotated as:


 * $\mathbf x = \left({x_1, x_2, \ldots, x_n}\right)$
 * $\vec x = \left({x_1, x_2, \ldots, x_n}\right)$
 * $\hat x = \left({x_1, x_2, \ldots, x_n}\right)$
 * $\underline x = \left({x_1, x_2, \ldots, x_n}\right)$
 * $\tilde x = \left({x_1, x_2, \ldots, x_n}\right)$

To emphasize the arrow interpretation of a vector, we can write:


 * $\mathbf{v} = \left [{x_1, x_2, \ldots, x_n}\right]$

or:


 * $\mathbf{v} = \left \langle{x_1, x_2, \ldots, x_n}\right \rangle$

In printed material the boldface $\mathbf x$ is common. This is the style encouraged and endorsed by this website.

However, for handwritten material (where boldface is difficult to render) it is usual to use the underline version $\underline x$.

Also found in handwritten work are the tilde version $\tilde x$ and arrow version $\vec x$, but as these are more intricate than the simple underline, they will only usually be found in fair copy.

The hat version $\hat x$ usually has a more specialized meaning, namely to symbolize a unit vector.

In computer-rendered materials, the arrow version $\vec x$ is popular, as it is descriptive and relatively unambiguous, and in $\LaTeX$ it is straightforward. However, it does not render well in all browsers, and is therefore (reluctantly) not recommended for use on this website.

Because of this method of rendition, some sources refer to vectors as arrows.

Comment
The reader should be aware that a vector in $\R^n$ is and only is an ordered $n$-tuple of $n$ real numbers. The geometric interpretations given above are only representations of vectors.

Further, the geometric interpretation of a vector is accurately described as the set of all  line segments equivalent to a given directed line segment, rather than any particular line segment.