Add tutorial demonstrating vector-valued random variables (Fixes #4007)

[Abhishek6122008]

This PR adds a new tutorial notebook demonstrating how to work with
vector-valued (shaped) random variables in PyMC.
It addresses feature request #4007.

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The notebook introduces a beginner-friendly example showing how to:

• define vector-valued mu and sigma parameters using shape=
• generate grouped data and integer labels
• use indexing (mu[data_labels], sigma[data_labels]) to map observations
  to the correct group parameters
• fit the model using pm.sample
• visualize posterior means vs. true simulated values

This notebook provides a simple, clear demonstration intended for new users.

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Notebook location

examples/howto/vector_variables.ipynb

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Checklist

• Notebook follows PyMC’s Jupyter style guide
  https://docs.pymc.io/en/latest/contributing/jupyter_style.html
• Linked to the relevant issue (#4007)
• Confirmed notebook is not excluded by pre-commit config
  https://github.com/pymc-devs/pymc-examples/blob/main/.pre-commit-config.yaml

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Any feedback and notices for further adjustments would be greatly appriciated as this is my first ever pr.

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