Courses I currently teach, with links to their course sites.
Each site is written for enrolled students in Japanese, and collects the slides, notebooks, and assignments for every session.
Intuition and experience fail systematically in front of data. Students learn statistics as a shared language for describing and reasoning about phenomena without cognitive bias, checking every idea by running it in Python rather than calculating by hand.
Builds the foundations of statistical inference with conditional probability, Bayes’ theorem, and probability distributions. Students then use simulation, information cascades, and Condorcet’s jury theorem to show how conformity breaks the independence of trials and degrades group decisions.
Methods for checking social phenomena against data, covering both quantitative and qualitative research. The course moves from the history and ethics of research and the use of official statistics to questionnaires, interviews, observation, and ethnography.
A project-based course in which each student carries out one survey over the semester: choosing a theme, writing questions, collecting and analysing responses, and publishing the results as a web page and a report. It also covers how to ask generative AI and how to check its answers.
The basics of data analysis in the behavioural sciences, taught in R (RStudio): importing, tidying, and visualising data, then running and interpreting t-tests, ANOVA, and chi-square tests. No prior programming experience is assumed.
The goal is not to memorise Word or Excel, but to decide what you want to do and to read and handle information correctly. The site keeps the materials for every session, along with NotebookLM slides, videos, and quizzes for review.
Practice problems matched to the Excel sessions. Runs in the browser.
OpenType the name of the prefecture that lights up on the map.
OpenTyping practice told as a short comedy series in eight episodes.
OpenAll course sites are in Japanese. A full teaching history is available on researchmap.