[MCMC] Add diagnostics and a potential sequal

[HumphreyYang]

These are summerized from a discussion with @jstac:

Some minor suggestions that we could add to the lecture on how to diagnose MCMC and where the Metropolis–Hastings algorithm may not perform well:

• Add trace plots for the JAX sampler under different proposal scales.
• Add autocorrelation plots for the same chains.
• Add a 2D correlated posterior example with contours and the chain trajectory overlaid.
• Use the 2D example to illustrate where random-walk Metropolis struggles in finite samples.

In the sequel, we could:

• Study how these issues motivate MALA and HMC/NUTS.
• Connect these algorithms to what is used in numpyro.

[jstac]

Many thanks for these great suggestions @HumphreyYang