This purpose of this article is to analyse relationship between single predictor variable (studytime, failures, absece, Medu, famsup, goout, higher) and dependent variable that has natural ordinal scale with more than two categories from target labels (low, medium, high). Datasets was given from student performance in secondary education (high school)

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.

The purpose of this article is to calculate eigenvalues, eigenvectors, the covariance matrix, and the correlation matrix for the Multivariate Analysis course assessment. Datasets was given from Credit Card Approval process.