This three-day workshop will focus on the discussion of the three main causes of the “replicability crisis” that social sciences are currently undergoing: 1) observations and experiments are carried out on samples that are too small to properly observe the investigated effects, 2) the current standard for claiming significant discoveries is based on p-values, which pose several problems (e.g. they do not indicate the size of the observed effects, they can suffer important alterations depending on small modifications of the data, eventually leading to “p-hacking”, and they are poorly understood by many researchers), and 3) strong pressure for publishing only significant results has lead to a publication bias caused by the reluctance to publish negative results, which precludes a great amount of relevant data highly needed to reject type I errors (i.e. false positives) from getting published.

Confirmed invited speakers

Harald Baayen (University of Tübingen)

Regina Nuzzo (Stanford University)

Joaquín Ordieres (Polytechnical University of Madrid)

David  Colquhoun (University College London)

Round table

Balthasar Bickel (University of Zurich)

Thoralf Mildenberger (Zurich University of Applied Sciences)

Maarloes Maathuis (ETH)

Tanja Samardžić (University of Zurich)

 

The workshop is especially aimed at doctoral and postdoctoral researchers. It has a strong practical focus, combining plenary conferences with short presentations by participants as well as practical sessions accompanied by the experts.

Funding by the UZH Graduate Campus via a GRC Grant is gratefully acknowledged.

Albert Wall

Carlota de Benito Moreno

Danae Pérez

	Wednesday October 4th (KAB-E-05)	Thursday October 5th (KAB-E-05)	Friday October 6th (RAA-E-27/RAA-E-08)
9:30-10:15	Introduction Carlota de Benito Moreno Danae Pérez Albert Wall	Plenary lecture Does data sampling matter at Big data scale? Joaquín Ordieres Meré (Polytechnical University of Madrid)	Plenary lecture P-values provide poor evidence: some proposals for improving reproducibility David Colquhoun (University College London)
10:15-11:00	Spatial statistics Curdin Derungs (University of Zurich)
11:00-11:30	Coffee break	Coffee break	Coffee break
11:30-13:00	Plenary lecture How not to fool yourself with statistics: Understanding and communicating p-values Regina Nuzzo (Stanford University)	Presentations by participants Axel Bohmann Haim Dubossarsky Katharine Dziuk Thoralf Mildenberger	Presentations by participants Ana Estrada Jerzy Gaszewski Dominique Hess & Tobias Leonhardt Sandra Schwab Hilary S.Z. Wynne & Swetlana Schuster
13:00-14:30	Lunch	Lunch	Lunch
14:30-16:00	Plenary lecture Regression modeling strategies for confirmatory and exploratory data analysis in the language sciences Harald Baayen (University of Tübingen)	Practical session 1	Practical session 3
16:00-16:30	Coffee break	Coffee break	Coffee break
16:30-18:00	Presentations by participants Abdulhameed Aldurayheem Nathalie Dherbey Chapuis Andreia Karnopp Hanna Ruch Kyoko Sugisaki	Practical session 2	Round table Balthasar Bickel (University of Zurich) Thoralf Mildenberger (Zurich University of Applied Sciences) Maarloes Maathuis (ETH) Tanja Samardžić (University of Zurich)

The workshop takes place in two different UZH buildings: KAB (Kantonsschulstrasse 3) and RAA (Rämistrasse 59).
Rooms:
KAB-E-05 (4-5 October) Check it on the map!
RAA-E-08 (6 October until 13:00) Check it on the map!

RAA-E-27 (6 October from 14:30) Check it on the map!

Here you can find some suggestions for your stay at Zurich.

Bed and Breakfast

• Francesco & Brigitta Di Bernardo, Im Wyl 42, CH-8055 Zürich
• Rosmarie Whiston, Lehfrauenweg 16, CH-8053 Zürich
  Eva Fritzsche, Gehrenholz E4, CH-8055 Zürich
• Regula Voerkel, Götzstrasse 15, CH-8006 Zürich

Hotels:

• Jugendherberge Zürich
• City Backpacker
• Hotel Foyer Hottingen
• Hotel St. Josef
• Hotel Sunnehus
• Hotel Marta
• Kafi Schnap
• Hotel Ibis/Novotel
• Hotel 25 hours
• Hotel Swissnight by Fassbind

Airbnb Zürich

 

On Tuesday 3rd October we'll be offering a Crash Course on R, so that those less familiarised with this programmation language feel more at ease when using it during the workshop.

Please install R and RStudio before attending the course and let us know if you have any trouble with the installation so that it can be fixed before the course starts.

During the course, we will focus on how to use R for data science. This means that we will not devote much time to explain the basis of R as a programming language. If you'd like to learn a bit more about this (this is not required for the course, but recommended either for before or afterwards!), we recommend you the package swirl. For doing so, please follow the instructions on the swirl website. In step 5, choose number 1 (“R Programming: The basics of programming in R”) and install it. You will get a good idea of how R works by completing lessons 1 to 7 (1: Basic Building Blocks; 2: Workspace and Files; 3: Sequences of Numbers; 4: Vectors; 5: Missing Values; 6: Subsetting Vectors; 7: Matrices and Data Frames). Have fun and contact us with any question!

Date and time: October 3rd 2017, 16:00 - 18:30.

Venue: KO2-F-173 (Karl-Schmid-Strasse 4)