Project implemented during master's studies, June 2024

Main goal: conducting cluster analysis of beers based on their physicochemical characteristics and technological parameters, such as initial density, final density, alcohol content, bitterness units and other important variables. The analysis aims to identify groups of similar beers, which will allow for classification and better understanding of the differences between different beer styles. The study also aims to check whether it is possible to distinguish two clusters that reflect the differences between top-fermented and low-fermented beers (basic classification of beers), and whether all beers of a given style fall into one cluster or are scattered between different groups.

Program used: RStudio

• projekt.Rmd

  Rmd file with data preparation to cluster analysis: description of variables, measurement scales, data imputation, extreme value analysis, selection of variables for study

• recipeData.csv & styleData.csv

  Files with data