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Teaching materials

Teaching portfolio

Here I make public a teaching portfolio that summarises a coherent set of materials representing my view of teaching as a scholarly activity, my professional experience and pedagogical training as well as some examples of course design.

Teaching resources

This section contains a variety of materials that I have used, developed and adapted for my seminars on research methods, agent based models and data collection and processing.

Module 1: Research methods using R

Lab 1: T-test and Simple linear regression. Download ipynb file

Lab 2: One-way ANOVA. Download ipynb file

Lab 3: Multiple regression. Download ipynb file

Module 2: Twitter data collection and analysis using R

Lab 4: Data collection and co-ocurrence analysis.

Module 3: Agent based models

Lab 5: Building a simple agent based model

Lab 6: Generating data using a cultral evolutionary model. In this lab we will use a version of the model published in Cognitive Science:

Scripts

Other external resources:

Research methods

Linear models and linear mixed effects models in R

Research methods in R

Agent-based modelling

A Short Tutorial on Agent Based Modeling in Python

Data collection and analysis

Digital Methods Initiative Twitter Capture and Analysis Toolset