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Course Registration & Tutorial PreferencesWritten on 07.04.26 by Pascal Schumann Dear students, Please remember to register for this course til Thursday, April 9 at 23:59. Moreover, registration for the tutorials is now open. Please submit your preferences under the Personal Status section. You can update your preferences until Friday, April 10 at 23:59. Additionally,… Read more Dear students, Please remember to register for this course til Thursday, April 9 at 23:59. Moreover, registration for the tutorials is now open. Please submit your preferences under the Personal Status section. You can update your preferences until Friday, April 10 at 23:59. Additionally, materials for the first unit have already been posted under Information --> Materials. There you can also find the slides from today's lecture covering the course organization. All the best, Statlab Team |
Course Goals
This course serves as an introduction to the fundamentals of statistics and probability theory and will cover most of the core principles of modern data analysis and predictive modeling.
Topics:
- Descriptive Statistics and Visualizations in Python
- Probabilities and Discrete Random Variables
- Continuous Random Variables and Laws of Large Numbers
- Parameter Estimation
- Statistical Testing
- Computer Simulations and Monte Carlo Methods
- Stochastic Processes
General Information:
The course follows an inverted classroom approach. It consists of weekly self-study using videos and lecture notes, tutorials, and self-study exercises using ALA. ALA is an AI chatbot specialized for this course that helps you practice and deepen your understanding of the material. The course is divided into three modules:
Module I: Descriptive Statistics, Probability & Random Variables
Module II: Distributions & Parameter Estimation
Module III: Statistical Testing
First session: Tuesday, April 7, 2026, 9:00 (organizational session, Günther-Hotz-Hörsaal)
Regular sessions begin the week of April 13.
Lecture Modalities
Each week consists of:
- Monday Lecture (GHH, Prof. Wolf): Large group session covering the week's material, including worked examples from the exercise sheet
- Tutorials (during the week): Small group sessions where you work on exercises from the previous week, discuss solutions, and take mini-tests
- Self-study with ALA: Practice exercises using ALA, an AI chatbot tailored to the course content that can guide you through problems and answer your questions
- Videos & Materials: New learning materials for self-study at home are released weekly
Exercise Sheets
- Each week, a comprehensive exercise sheet is provided. Parts of it will be used across all modalities: ALA, Monday Lecture, Tutorials
- Weekly mini-tests
- Group work on the exercise sheet problems
Office Hours
TBA
Q&A
- Attendance at the tutorials is mandatory and verified through submission of mini-tests and completed exercises.
- First session on April 7 at 9:00: Introduction and organization of the course.
- Regular schedule begins on April 13.
- Exam is on July 13th.
Exam Admission: To be admitted to the final exam, you must
- complete the exercises and mini-tests in the tutorials (percentage will be announced)
- submit several dialogues with ALA
More details will be announced at the organizational session on April 7.