This repository is intended to provide an example of a simple bayesian workflow including data cleaning, imputation of missing values, model specification, model criticism, and data visualization.
This project was developed as part of the final assessment for PSYC 4960: Bayesian Data Analysis at Rensselaer Polytechnic Institute (RPI) and is made publicly available following my completion of the course. While this repository falls under an MIT license, reuse of any materials contained within for assignments pertaining to this course is prohibited and may result in an academic integrity violation.
This code accompanies the following paper which formally reports the analyses conducted via the R script. All generated plots and graphics are also presented within. The data used for these analysis are synthetic and were sourced from kaggle here.
The code can be downloaded and run as-is to reproduce the results reported in the included paper. A copy of the dataset is included in the Data folder and the script expects to find this folder one level above the directory where student_performance_analyis.R is located. It is reccomended to simply download the repository and run the script.