Article informative priors

[cetagostini-wise]

Changes log:

• Correction of strings style by @juanitorduz

• Correction of causalpy plot dates style by @juanitorduz

• Correction of derivative plot legends by @juanitorduz

• Recommendation about utilise pm.find_constrained_prior by @juanitorduz

• Recommendation about reference article by @juanitorduz

• Applying Isort & Ruff by @juanitorduz and @wd60622

• Correction in the narrative to create a more engaging content and skip the DGP by @ulfaslak & @drbenvincent

• Deeper explanation about how we are using CausalPy to estimate the total effect @drbenvincent

• Deeper explanation about how to find the prior values by @wd60622

[juanitorduz]

@twiecki would it be possible to allow the ReviewNB for this repository so that we can provide feedback on the notebook directly 🙏 ?

[aloctavodia]

If adding ReviewNB is not possible a workaround is to use jupytext to automatically generate .md files. Not at nice as ReviewNB, but reading and commenting .md files is better than just notebooks.

[review-notebook-app]

Check out this pull request on 

See visual diffs & provide feedback on Jupyter Notebooks.

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[twiecki]

added

[cetagostini-wise]

@juanitorduz You ask to add uncertainty in the prior plots but, I didn't add it in the plots because the intervals are to wide and makes the images look very strange, and pick a lower interval could be seeing as guiding the information in a "convenient" way at best.