Experimental Design and Analysis

Caroline Appert

Class material

Class 1: Introduction to Experimental Design (Slides and Videos used in slides)
Class 2: Statistical analyses for Laboratory Experiments (Slides)
Class 3: Hands-on approach to Experimental Design (Slides and Videos used in slides)
- Touchstone 2: online tool, introduction video, and XML export for the example used in slides
Class 4: Experiment Programming (Slides)
- Project start code: Download
Class 5: Introduction to Jupyter and Descriptive Statistics (Slides and Video used in slides)
- Notebook with all examples used in slides: Download
Class 6: Inferential Statistics (Slides)

Project

IMPORTANT: Register your group in this spreadsheet.

Reports are due March 10 by email to caroline.appert@universite-paris-saclay.fr

A report consists of three files:

Log files (CSV format)
Jupyter notebook with statistical analyses (ipynb format)
Report (PDF format). The report should be concise, and its structure should be as follows:
1. Short introduction: describe experiment goal.
2. Hypotheses: state the hypotheses to test.
3. Operationalization: detail rationale for choosing factors, measures, and experimental task. In other words, explain why these specific factors, measures and task will allow you to test your hypotheses (we address this together in class -- pay attention).
4. Procedure: specify the type of design, the number of participants, the number of task replications, the task presentation order, etc.
5. Participants: describe the population sample who participated in your experiment.
6. Apparatus: describe the hardware used for your experiment
7. Results: report on your statistical analyses and do not forget to interpret them with respect to the stated hypotheses (i.e., answer the question "do they support or reject your hypotheses?")
8. Short conclusion: what worked well, what the potential limits and threats of validity are, etc.