https://github.com/adrn/princetonstatsseminar

Supplementary material for my lecture on 6 Feb.
https://github.com/adrn/princetonstatsseminar

adrn-teaching bayesian-inference probability python statistics

Last synced: 12 days ago
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Supplementary material for my lecture on 6 Feb.

• Host: GitHub
• URL: https://github.com/adrn/princetonstatsseminar
• Owner: adrn
• License: mit
• Created: 2017-01-29T23:36:06.000Z (about 8 years ago)
• Default Branch: main
• Last Pushed: 2020-06-21T15:11:33.000Z (over 4 years ago)
• Last Synced: 2024-12-02T21:42:15.645Z (2 months ago)
• Topics: adrn-teaching, bayesian-inference, probability, python, statistics
• Language: Jupyter Notebook
• Homepage:
• Size: 4.05 MB
• Stars: 2
• Watchers: 5
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Princeton Stats Workshop (6 Feb)

Supplementary material for my lecture on model fitting.

# Dependencies

I recommend using [anaconda](https://anaconda.org/) as your Python distribution and package

manager. (If you don't already use it, you can download it and install a new version of Python

pretty harmlessly. It will install everything to a new directory so it won't mess with your

existing installation). One of the great advantages of Anaconda is the ability to create [conda

environments](https://conda.io/docs/using/envs.html) that let you maintain different, independent

Python installations (e.g., you can have Python 2 and 3 installed in parallel) and easily switch

between them. I recommend creating a new environment for this material with all of the packages

we'll need, just to sandbox everything and make sure we're all using the same versions. If you

clone or download this repo, you can use the

[environment.yml](https://github.com/adrn/PrincetonStatsSeminar/blob/master/environment.yml) file

to automatically create the environment for you. After cloning / downloading, change directories

into the project root and do:

    conda env create

Once that's done installing everything, you need to activate the environment to use the version of

Python with all of the packages it just installed. Do that with:

    source activate statsseminar

To deactivate the environment (if you want to go back to your root environment / default context)

you just have to do:

    source deactivate