CPHA has also developed training and resources on the statistical programming language R. These trainings encourage Stata and SAS users to transition to R for their data analysis and computation. R’s benefits in terms of collaboration, big data analysis and cloud computing make it well-suited to the future of demographic and social science research.
CPHA offers R-specific training courses:
An Introduction to R is suited for Stata and SAS users and it provides an overview of R’s syntax and benefits. It explores data types, data manipulation, regression, graphics and programming. The training includes hands-on examples and exercises with real-world data.
Collecting Web-Based Data Using R covers making HTTP requests, web scraping, working with structured or scraped web data, interacting with APIs and obtaining open data.
Text Analysis Using R explores data import and formatting, cleaning and prepping documents, data visualization, exploratory analysis, basic network analysis and topic modeling.
Working with Big Data, SQL, and Cloud Computing using R provides an introduction to working with remote structured databases, performing SQL queries, and accessing and using cloud computing services like Amazon Web Services and Google Cloud Compute Engine.
Generalized Linear Models in R, covers the basics of running GLMs in R, including specification and syntax, interpretation and displaying of results, and model checking. We will examine binary, count, and categorical models.
Multilevel Modeling in R, covers the basics of running multilevel models in R, including specification and syntax, interpretation and displaying of results, and model checking and comparison.
For all of these trainings, R scripts, code, data, reports and presentations are available for download. Materials have been created from the ground up, to ensure the inclusion of the newest techniques in R.