Global Studies Method Track Website

This website contains a collection of tutorials, developed at the University of Maastricht for our students in Global Studies that use python.

The goal is to organize relevant material for quantitative methods in an efficient manner, that can be findable, accessible and reusable to students during and after their studies, and can be used across semesters.

Tutorial 1

Today is an introduction to statistics and coding in Python for our students in Global Studies. This tutorial references JupyterLab but can be taught using a regular Python interpreter as well as Google Colab. Please note that this tutorial uses Python 3.

Jupyter Notebooks

Variables and basic operations - ✔️ Solutions
Data Types - ✔️ Solutions
Built-in functions and libraries - ✔️ Solutions
For Loops and List - ✔️ Solutions
Customized functions - ✔️ Solutions

Tutorial 2

This week’s tutorial covers how to access already existing data sources and how to store the data using Pandas library. You will learn how to generate data from distributions and how to sample using the Numpy library. You will learn the differences between true-positive and false-positive conclusions.

Jupyter Notebooks

Distributions and Sampling with Numpy - ✔️ Solutions
Dataframes and Confusion Matrix with Pandas - ✔️ Solutions

Tutorial 3

In this week’s tutorial, you will practice with NHST. In particular, you will run t-tests for independent groups using Python and the Jupyter notebook. You will learn how to obtain and interpret p-values and how to substantially interpret statistical results.

Jupyter Notebooks

Introduction to Null Hypothesis Significance Test - ✔️ Solutions

Tutorial 4

During this week’s session, you will use provided datasets to conduct t-tests for correlations and dependence between two variables. You will learn how to interpret the p-value and how to relate the statistical conclusions.

Jupyter Notebooks

Complex Null Hypothesis Significance Test - ✔️ Solutions

Tutorial 5

In this visualization lab, you will learn how to make interactive charts. Additionally, you will learn how to create correlation matrices, which represent the relationships between variables.

Jupyter Notebooks

License

Code

The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.

Text

The text content of the book is released under the CC-BY-NC-ND license. Read more at Creative Commons.