QuantEcon / QuantEcon/lecture-python-intro
Add a lecture on correlation vs causation
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new-lecture
- Dominant language
- Jupyter Notebook
- Stars
- 65
- Forks
- 32
- Avg merge
- 4d 14h
- Merged PRs (30d)
- 6
Description
Key ideas
- use relevant economic applications
- begin with graphical analysis
- add some kind of statistical analysis that confirms the ideas in the figures.
Seeking applications from Ippei Fujiwara (Keio)
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No lecture notebook, test, or entry point is named in the issue. Review the existing lecture structure first, then define an economic application with graphical analysis and statistical analysis that supports the figures; completion should include a coherent lecture covering correlation versus causation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- content, data-visualization, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100