https://github.com/monika76five/Undergrad-Bayesian-Course

https://github.com/monika76five/Undergrad-Bayesian-Course

Last synced: 3 months ago
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• Host: GitHub
• URL: https://github.com/monika76five/Undergrad-Bayesian-Course
• Owner: monika76five
• Created: 2019-08-22T02:42:48.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-11-21T22:41:25.000Z (almost 4 years ago)
• Last Synced: 2024-05-31T21:02:21.198Z (6 months ago)
• Language: TeX
• Size: 8.79 MB
• Stars: 60
• Watchers: 4
• Forks: 28
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# An Undergraduate Bayesian Statistics Course

- Textbook: Probability and Bayesian Modeling (1st Edition), Albert and Hu, Chapman & Hall/CRC Texts in Statistical Science.

    - [Book website](https://monika76five.github.io/ProbBayes/)

    

    - [CRC Page for the Book](https://www.crcpress.com/Probability-and-Bayesian-Modeling/Albert-Hu/p/book/9781138492561)

- Computing resources

    - The ProbBayes R package

        - Installing from CRAN link

        ```{r, eval = FALSE}

        install.packages("ProbBayes")

        library(ProbBayes)

        ```

        

        - Installing from Github

        ```{r, eval = FALSE}

        devtools::install_github("bayesball/ProbBayes")

        require(ProbBayes)

        ```

    

    - JAGS (Just Another Gibbs Sampler)

    

        - Downloading and installing: [sourceforge link](https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/)

        

        - The runjags R package

        ```{r, eval = FALSE}

        install.packages("runjags")

        require(runjags)

        ```

    

- Pre-requisites

    - Coursework: college-level Multivariate Calculus, Linear Algebra, and Probability

    

    - Computing in R: equivalent to DataCamp's

    

        - Introduction to R: [DataCamp link](https://www.datacamp.com/courses/free-introduction-to-r)

        - Intermediate R: [DataCamp link](https://www.datacamp.com/courses/intermediate-r)

        - Introduction to the Tidyverse: [DataCamp link](https://www.datacamp.com/courses/introduction-to-the-tidyverse)

- Teaching and learning material (Fall 2019 iteration of MATH 347 Bayesian Statistics at Vassar College, NY)

    

    - Lectures folder: lecture files (.Rmd and .pdf).

    

    - Homework folder: homework files (.tex and .pdf).

    

    - Labs folder: lab files (.Rmd and .pdf).

    

    - Case Studies folder: case study files (.tex and .pdf).

    

    - Lecture recordings available at [this complete YouTube playlist](https://www.youtube.com/playlist?list=PL_lWxa4iVNt1TfbsAfv9aW_5KL9rZuAtr).