Hier ist die Aufgabenstellung der Korrekturen, die du vom Anfangsskript (R-Tutorial-ST-before-Class-2025-04-07a-BS.Rmd) bis zum finalen Ergebnis vornehmen musst.

Goethe University Frankfurt Preparation - Workspace and Notation Read and Describe Data Variables Selection Hierarchical Clustering 5 Hierarchical Clustering Perform Hierarchical Clustering Run Clustering with Ward Method Derivation of Number of Clusters Dendrogram Elbow-Criterion Save Cluster Assignments Cluster Description Erstelle die Mittelwerte pro Cluster Profile Customers for Targeting Partitional Clustering (here: K-Means) Set Seed Example: Kmeans for 5 Clusters

Introduction to R and RStudio lecture for the 1st year students of Life Sciences and Chemistry Major

This project implements a complete computational framework for CAT, bridging the robust mathematical foundations of Item Response Theory (IRT) with the dynamic, data-driven logic of adaptive algorithms. By continuously selecting the most informative items for each individual, CAT achieves precise ability estimation with substantially fewer questions, reducing testing time by 50–70% while maintaining or enhancing measurement quality. The system integrates core components—from Fisher Information and Bayesian estimation to practical constraints like content balancing and exposure control—into a cohesive, operational engine for next-generation educational, psychological, and professional assessment.

2026-02-04

This interactive web presentation explores key relationships between automotive performance metrics using R Markdown and Plotly. Through dynamic visualizations, discover how horsepower impacts fuel efficiency, how cylinder count affects MPG, and the distribution of vehicle weights. With fully interactive plots that allow zooming, panning, and hovering for detailed insights, this project demonstrates modern data visualization techniques for communicating complex automotive data in an engaging and accessible way.