pymdownx.arithmatex
For maths lovers
The pymdownx.arithmatex extension is a Python-Markdown plugin that enables rendering of mathematical expressions written in LaTeX syntax.
Configuration
# mkdocs.yml
markdown_extensions:
- codehilite
Note:
When pymdownx.arithmatex is enabled, the theme automatically
loads KateX material to render math (css, js and fonts).
Currently we ship the version v0.16.21.
Syntax
Just like latex.
Let $F$ be a primitive of $f$,
$$
\int_{a}^b f(x) ~\mathrm{d}x = F(b) - F(a).
$$
Let \(F\) be a primitive of \(f\),
You can combine with admonition for instance.
!!! note "Theorem"
Let $X_1, X_2, \dots, X_n$ be a sequence of independent and
identically distributed random variables with mean $\mu$ and
finite variance $\sigma^2$. Define the sample mean:
$$
\overline{X}_n = \frac{1}{n}\sum_{i=1}^{n} X_i
$$
Then, as $n \to \infty$:
$$
\frac{\sqrt{n}(\overline{X}_n - \mu)}{\sigma} \xrightarrow{d} \mathcal{N}(0,1)
$$
In other words, the distribution of the standardized
sample mean approaches the standard normal distribution:
$$
\frac{\overline{X}_n - \mu}{\sigma/\sqrt{n}} \xrightarrow{d} \mathcal{N}(0,1), \quad \text{as } n \to \infty
$$
Theorem
Let \(X_1, X_2, \dots, X_n\) be a sequence of independent and identically distributed random variables with mean \(\mu\) and finite variance \(\sigma^2\). Define the sample mean:
Then, as \(n \to \infty\):
In other words, the distribution of the standardized sample mean approaches the standard normal distribution: