How can journalists use data to find stories? How can they tell stories through data? This online course provides students and practitioners with the knowledge and skills necessary to begin gathering, analyzing and visualizing interactive, data-driven stories. Prior experience with advanced statistics, web design or computer programming is neither assumed nor necessary to succeed in this course. Instead, it covers, at an introductory level, key principles pertaining to programming, descriptive statistical analysis, and information visualization and design.
This online course is designed to leverage free tools that are now standard in the workflows of many data journalists. The course provides short, instructional videos that introduce ideas and concepts; tutorials using the R statistical programming language; and a few data challenges that task you with answering questions using publicly accessible datasets.
By the end of this course, you will be able to: (1) generate story ideas that may be addressed through analyses of publicly accessible data; (2) locate sources of public data; (3) evaluate the strengths and weaknesses of data sources and datasets; (4) identify errors in data files and "clean" them; (5) apply computer science fundamentals using the R scripting language; (6) analyze data using descriptive statistical techniques to identify patterns, groups, potential relationships; and outliers of interest; and (7) create interactive data visualizations.
When you're ready to begin, head over to the Modules page.
The materials created by the Instructor are governed by the CC BY-SA 4.0 license. This means that you may copy and redistribute the material in any medium or format, and that you may remix, transform, and build upon the material for any purpose, even commercially. However, any reuse must include appropriate credit and derivatives must adhere to a compatible license.
Any third-party materials (including datasets) provided on this page are subject to their original license.