Conditional vs Interventional Distribution (#552)

* initial commit of interventional notebook

* various improvements

* add do operator section + updated plot formatting + do operator presentation

* add references

* minor edits

* add more take away lessons at the end of the notebook + add more references

* more maths info about factorising the joint distributions

* add random seed to all sampling for total reproducibility

* add note to clarify we are not doing inference/estimation

* fix typo

* pimp the introduction

* Add a bunch more intro information

* additional explanatory and introductory text

* change title

* add callout box for the importance of the DAG scripts

* better transition to conditional distributions

* try to fix links to other pymc-examples notebooks

* second attempt to fix links to other pymc-examples notebooks

* third time luck fixing internal links to other pymc-examples

* whitebox -> white box

* pimp the summary. Add a new tag

* use datasets directly instead of intermediate df conversion

* rerun notebooks to make tests pass

* Update examples/causal_inference/interventional_distribution.myst.md

Co-authored-by: Oriol Abril-Pla <[email protected]>

* multiple edits for Oriol

* wording fix + set hdi_prob=1.0 to avoid truncation in the final plot

* DAGS -> DAGs

* multiple instances of mutilation -> mutation

* remove specific admonition block about pymc_experimental

* minor re-wording

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Co-authored-by: Oriol (ZBook) <[email protected]>

Author: drbenvincent