Data Analysis

These guides are meant to take you step by step on how to use R to analyze your data. Each module provides example code that shows you how to run functions relevant to your analysis. The data sets used in these modules are linked below, feel free to download the data sets and follow along on your own computer.

Data Carpentry workshop lesson plans can be used for self-guided learning. They are domain-specific, so that we are teaching researchers the skills most relevant to their domain and using examples from their type of work.

An OER that covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.

Numerous cheatsheets to help you remember what functions to use in what library, based on thematic topic (such as tidying or graphing data).

The Text Analysis Pedagogy Institute is an open educational institute for the benefit of teachers (and aspiring teachers) of text analysis in the digital humanities and data science. This site contains links to the workshops for the institute and intends to: Help train teachers in text analysis; Share computational text analysis lessons in an Open Educational Directory; Serve as a template for your own teacher workshops and courses

Constellate offers open educational lessons for text analysis using Python. It is a platform for teaching, learning, and performing text analysis using the world’s leading archival repositories of scholarly and primary source content.

This website hosts a free online textbook, Introduction to Cultural Analytics & Python, which offers an introduction to the programming language Python that is specifically designed for people interested in the humanities and social sciences. This book demonstrates how Python can be used to study cultural materials such as song lyrics, short stories, newspaper articles, tweets, Reddit posts, and film screenplays. It also introduces computational methods such as web scraping, APIs, topic modeling, Named Entity Recognition (NER), network analysis, and mapping.

Check here for examples of data projects that took data and used Python to answer a research question. Code walkthrough is included.