This repository contains the lecture notes and other materials for the course “Experiment Design in Computer Science (0AL0400)”, as taught at The University of Tsukuba, Department of Computer Sciences.
About this Course
The collection and analysis of data through experiments is one of the cornerstones of the scientific method.
This course aims to educate students about how to conduct good scientific experiments, and how to use statistical tools to analyze data obtained from these experiments.
The contents of this course focus on Computer Science experiments, although the topics can be applied to other disciplines as well.
You can see more information in the full syllabus of the course.
Topic 0: Introduction and Housekeeping
Topic 1: What is Experimentalism
Topic 2: Point and Interval Indicators.
Topic 3: Inference Testing I – Hypothesis testing.
Topic 4: Inference Testing II – Comparison testing and Paired testing.
Topic 5: Inference Testing III – Non-normality and Anova for Multiple comparison
Topic 6: Sample Size Calculations
Topic 7/8: Experimental Factors
University of Tsukuba Students will want to check out the manaba page for this course to submit feedback surveys and reports.
The useful links page contains other online resources that will give you an increased understanding of the topics in this course. Make sure to check it out!
This course was forked from and follows closely the “Design and Analysis of Experiments” material by Felipe Campelo (Aston University) BY-NC-SA 4.0
Citation and License
This material is licensed Creative Commons BY-NC-SA 4.0. You are free to use and modify the Lecture Notes as you see fit, for any purpose, as long as you share your modified materials equally (I would love to hear about it if you remix this). If you find any errors, or have ideas for improvements, I would appreciate if you could mention it as an issue in this repository.