The norm of a vector $(1,3,4,11,13)$ is $\sqrt{1^2+3^2+4^2+11^2+13^2}$. It is an extension of Pythagoras' Theorem.


To elaborate on my comment on Michael's answer:

The symbol $\left\Vert\mathbf{u}\right\Vert$ for a vetor $\mathbf{u}$ usually stands for the norm of that vector. A norm is "a function that assigns a strictly positive length or size to each vector in a vector space" (quoted from wikipedia).

Having a normed vector space enables you to talk about e.g. the length of a vector. A common example would be the vector space $\mathbb R^n$ with the euclidean norm which is the norm induced by the dot product $\langle v,w\rangle = \sum\limits_{i=1}^n v_iw_i$ where $v=\begin{pmatrix} v_1 \\ \vdots \\ v_n \end{pmatrix},w=\begin{pmatrix} w_1 \\ \dots \\ w_n\end{pmatrix}$, but there are other norms and inner products one can use.

Let $\mathcal V$ be a vector space with $\dim(\mathcal V)=n$ over $\mathbb R$ and $\langle\cdot,\cdot\rangle$ an inner product on $\mathcal V$. Then $(\mathcal V,\left\Vert\cdot\right\Vert)$ is a normed vector space with $\left\Vert v\right\Vert:= \sqrt{\langle v,v\rangle}$. The norm of a vector can be interpreted as the length of the vector but it is dependent on which inner product one uses.