The purpose of this publication is to explore the application of multinomial logistic regression in predicting the type of glass based on chemical composition features. The study aims to analyze the influence of various chemical properties, such as RI, Na, Mg, Al, and Ca, on the differentiation between different glass types. By understanding the predictive power of these variables, the research seeks to contribute to the field of material classification and enhance the accuracy of predictions for industrial processes related to glass production. Additionally, this publication addresses the challenges faced in classifying certain glass types, such as "vehicle_float" and "headlamps," and provides insights into potential improvements for model performance.

develop a script in R to create a violin plot displaying the distribution poof a continuous variable with separate violins for each group using ggplot2

To generate a basic box plot using ggplot2, enhanced with notches and outliers and grouped by using a categorical variable using the in-built dataset in R.

To generate a basic box plot using ggplot2, enhanced with notches and outliers, and grouped by a categorical variable using an in-built dataset in R.

Write an R program to create multiple dot plots for grouped data , comparing the distribution of variable across different using ggplot2’s position dodge function .