DAS-Group-15
The FILE aims to investigate the relationship between different coffee features and the overall quality classification of a coffee batch. We intend to use a Generalised Linear Model (GLM) to explore how variables such as country of origin, aroma, flavor, acidity, category two defects, mean altitude of the growers' farm, and harvest year, affect the likelihood of a coffee batch being classified as either good or poor.
Before you begin, ensure you have the following prerequisites installed and set up:
*R: The programming language used for statistical analysis. Make sure you have the latest version of R installed on your machine. *RStudio: An integrated development environment (IDE) for R. It is recommended for running R scripts, although you can use any R-compatible interface. *Operating System: The scripts should run on any operating system that supports R, including Windows, macOS, and Linux.
The following R packages (libraries) are used in the project:
*tidyverse: An opinionated collection of R packages designed for data science. *moderndive: Used for data analysis and visualization, especially for introductory statistics. *gapminder: Contains a dataset for demonstration purposes. *sjPlot: Useful for creating tabular and graphical summaries of data. *stats: Provides functions for statistical calculations, included by default in R. *jtools: Tools for summarizing and visualizing regression analysis. *gridExtra: Assists in arranging ggplot2 graphs on a page. *skimr: Provides compact and flexible summaries of data. *gt: Offers functions to create display tables for data frames. *GGally: Extends ggplot2 for easy creation of complex plots like pairs plots.
You can find the DAS-Group-15 documentation on the website.
React is MIT licensed.