Crash Course in Statistics for Neuroscience Center Zurich, University of Zurich, Summer 2026

[2 credit points]

If you miss more than 6 h (two half days) of Course, you don't get any CP's!; in detail:

• Max. allowed absence for the theoretical part (Christoph Luchsinger): One morning
• Max. allowed absence for the "Applications in R" part (Zofia Baranczuk): One morning OR 1 afternoon

Time:

Date	Time	Lecturer	Subject	Venue
August 17	0900-1200	Dr. Christoph Luchsinger	Theory	Y13 L-11/13
August 18	0900-1200	Dr. Christoph Luchsinger	Theory	Y13 L-11/13
August 19	0900-1200	Dr. Christoph Luchsinger	Theory	Y13 L-11/13
August 20	0900-1200	Dr. Christoph Luchsinger	Theory	Y13 L-11/13
August 21	0900-1200	Dr. Christoph Luchsinger	Theory	Y13 L-11/13
		Below dates might shift slightly
August 24	0900-1200 and 1300-1600	Dr. Zofia Baranczuk	Applications (in R)	Y13 L-11/13
August 25	0900-1200	Dr. Zofia Baranczuk	Applications (in R)	Y13 L-11/13
August 26	0900-1200	Dr. Zofia Baranczuk	Applications (in R)	Y13 L-11/13
August 27	0900-1200	Dr. Zofia Baranczuk	Applications (in R)	Y13 L-11/13

Lecturers:

• Dr. Christoph Luchsinger, 076 392 03 20, christoph.luchsinger@math.uzh.ch
• Dr. Zofia Baranczuk, zofia.baranczuk@math.uzh.ch

Aims of the Course: Participants...

1. have basic knowledge of probability theory
2. can solve simple statistical problems without help
3. can reconstruct the train of thought of correct solutions to more complicated problems and adapt them to their own problems with same structure
4. have basic knowledge of statistics, enabling them to familiarize themselves with more advanced topics in the literature given below
5. have R-Documentation to methods treated (no complete introduction!)
6. see limitations of statistical reasoning

The way this course is taught

This course will be split into a theoretical part (17th to 21st of August) taught by Christoph Luchsinger and an applied part (24th to 27th of August) taught by Zofia Baranczuk.

How to prepare for the applied part:

• Install R & RStudio – there are many guides on the internet on how to do it.
• A script containing documentation, comments and exercises, as well as the slides of the theoretical parts in the mornings, will be made available at the beginning of the course.
• The lecturer will be coaching the participants on the tasks they will solve such that everyone can work with their own speed.

Contents / Downloads (Script):

Christoph Luchsinger

1. Introduction
2. Distributions
3. Visualization
4. Tests, Models
5. Diagnostics Issues

Exercises - to be handed in by midnight each day

• Exercises for chapter 1
• Exercises for chapter 2
• No explicit exercises for chapter 3 - covered by applied part
• Exercises for chapter 4

Zofia Baranczuk

All material for the practical part can be found under the following link.

Prerequisites:

• BSc/MSc or PhD Natural Science, Pharmacy, Medicine
• 1 Semester of Introductory Probability Theory and Statistics or extremly motivated and numbers loving

suggested Literature and preparation: Script and in particular the following books:

• easy to read: The cartoon guide to Statistics by L. Gonick and W. Smith, HarperPerennial - same in German: Statistik in Cartoons L. Gonick und W. Smith
• more serious: Statistische Datenanalyse by W.A. Stahel (ETH Zürich), Vieweg
• Something in English: Fundamental Concepts in the Design of Experiments by C.R. Hicks, Oxford University Press, New York, 1993

• Suggested preparation I: Stahel Chapter 1-6; or Cartoon Guide Chapter 1-5 (easy to read).
• Suggested preparation II: For further background reading, we recommend the open and free online statistics resources provided by the Penn State University: https://online.stat.psu.edu/statprogram/.

Links:

• Course each summer for basic Maths (choose the first course)
• Script for BSc students of Science at Stochastik für die Naturwissenschaften, go to "Details"
• List of Consulting Services
• Consulting Services at
  • University of Zurich
  • ETHZ