Statistics with R: Data Analysis and Inference

Dr. Christophe Smet serves as a distinguished lecturer at TU Delft, specializing in teaching bachelor-level courses in Probability Theory, Statistics, Calculus, and Linear Algebra. He has made significant contributions to mathematics education, notably leading the development of an extensive collection of 535 open-access Linear Algebra exercises that benefit engineering students across multiple disciplines. His academic journey includes teaching experiences at the universities of Leuven and Antwerp, with his doctoral research focused on Classical Analysis, particularly investigating techniques for proving the irrationality of constants. While his initial research centered on orthogonal polynomials and Painlevé equations, his interests have evolved to encompass both particle physics and astrophysics. At TU Delft, he actively participates in creating innovative educational content, including parameterized exercises that allow students to practice with varying values, and has been instrumental in developing comprehensive probability theory courses that cover everything from basic concepts to advanced applications in engineering

Dr. Rik Lopuhaä serves as an Associate Professor in the Section of Statistics at TU Delft's Delft Institute of Applied Mathematics, where he has established himself as a leading expert in mathematical statistics. After completing his mathematics studies at the University of Amsterdam, he earned his PhD from TU Delft, specializing in robust multivariate statistical methods. His research focuses on asymptotic theory for statistical methods, particularly in shape-constrained nonparametric methods and robust multivariate analysis. As an educator, he has developed numerous statistics courses and achieved significant recognition as co-author of the widely-used Springer textbook "A Modern Introduction to Probability and Statistics: Understanding Why and How." His teaching portfolio spans various departments at TU Delft and includes collaborations with industry partners. At the university, he actively contributes to academic development through teaching, student supervision, and research activities, while also supporting researchers through the Statistics Helpdesk, where he provides guidance on statistical aspects of research projects.

Professor Annoesjka Cabo stands as a distinguished figure at TU Delft, serving as both the Academic Director of the Teaching Academy and Director of Education at the Faculty of Electrical Engineering, Mathematics and Computer Science since July 2021. Her expertise centers on Statistics for Innovation in Education, where she leads groundbreaking initiatives in mathematics education reform. She has spearheaded the PRoject Innovation Mathematics Education (PRIME), a comprehensive program aimed at redesigning mathematics courses for engineering students through blended learning approaches. Her significant contributions include implementing the "Prepare, Participate, Practice" methodology, which has demonstrably improved student engagement and academic performance across multiple engineering disciplines. As the Academic Director of the Teaching Academy, she oversees four key elements: Community, Teaching Lab, Programme, and Facilitation Team, working to enhance engineering education through innovation and collaboration. Her research focuses on developing statistical models to measure the effectiveness of educational innovations, particularly in mathematics education, and her work has significantly influenced how engineering mathematics is taught at TU Delft, leading to improved student outcomes and more effective teaching methodologies.