If you miss more than 3 h (half day) of Course, you don't get any CP's!

Time:

Date	Time	Lecturer	Subject	Venue
August 21	0900-1200	Dr. Christoph Luchsinger	Theory	Y03 G-85 (Irchel-Campus)
August 22	0900-1200	Dr. Christoph Luchsinger	Theory	Y03 G-85 (Irchel-Campus)
August 23	0900-1200	Dr. Christoph Luchsinger	Theory	Y03 G-85 (Irchel-Campus)
August 24	0900-1200	Dr. Christoph Luchsinger	Theory	Y03 G-85 (Irchel-Campus)
August 25	0900-1200	Dr. Christoph Luchsinger	Theory	Y03 G-85 (Irchel-Campus)
August 28	0900-1200 und 1300-1600	Servan Grüninger	Applications (in R)	Y03 G-85 (Irchel-Campus)
August 29	0900-1200 und 1300-1600	Servan Grüninger	Applications (in R)	Y03 G-85 (Irchel-Campus)
August 30	0900-1200	Servan Grüninger	Applications (in R)	Y03 G-85 (Irchel-Campus)

Lecturers:

• Dr. Christoph Luchsinger, 043 243 15 08, chris@acad.jobs
• Servan Grüninger, servan.grueninger@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 (22 to 26th of August) taught by Christoph Luchsinger and an applied part (29th to 31st of August) taught by Servan Grüninger.

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

Solutions

• Solutions exercises for chapter 1
• Solutions exercises for chapter 2
• Solutions exercises for chapter 3-5

Servan Grüninger

All material for the practical part can be found under the following link: www.servangrueninger.ch/znz22 (from the 26th of August onwards)

Prerequisites:

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

Administration/Registration: Heidi Gauss, hgauss@neuroscience.uzh.ch, Tel. 044 635 33 82

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 second course)
• Script for BSc students of Science at Stochastik für die Naturwissenschaften
• List of Consulting Services
• Consulting Services at
  • University of Zurich, General Consulting
  • University of Zurich, Animal Research Consulting
  • ETHZ

Webmaster: Dr. Christoph Luchsinger / chris@acad.jobs