Data Storytelling
Our lives are driven by data and facts and so is the world. Doctors ponder over lab results while patients nervously await their conclusions; politicians worry about polls and unemployment rates; scientists warn of rising global temperatures; managers obsess about performance indicators; students about grades; instructors about their evaluations. Data communication is the lubricant of everyday life.
Good, useful data should always be part of an argument. Thus, data needs to be organized and delivered within a coherent story. However, what makes a good data story? We believe, and we will help you learn how and why, data stories should surprise, should provide a new, more convincing explanation for time-worn ideas, and should propose a course of action.
The primary assumption of our course is that the goal of communicating with data is ultimately to identify causal mechanisms and change the status quo due to the obtained insights. All audiences have previous understandings of the world, and meaningful data stories should challenge their assumptions about that world. This is best accomplished through a story. In other words, this communication assumes the form of a story, which is defined as the narrative of how an unexpected cause creates an effect. Therefore, stories teach. Our goal is to train you in making memorable, teachable arguments by telling them in the form of stories.
This program is a series of four courses available 100% online. The courses are self-paced and you have 12 weeks of access to complete each course once you start. The full certificate can be earned within a year. Students can register for the courses individually, or purchase all four to earn a Data Storytelling certificate from Purdue. Data Storytelling 101 is a free course that must be taken before you start any of the other paid courses.
Data Storytelling Courses Available
Data Storytelling 101
This course is free with the purchase of a paid course.
Data Storytelling 101 offers an introduction to the concept of Data Storytelling, why it matters, and how it can transform the results of your research into impactful narratives from which your audience learns new things, remembers important findings, and acts on them. This course must be taken before you start any of the other paid courses.
Learning outcomes:
- Provide examples and justify all core techniques in storytelling, including challenging prior assumptions, providing alternative explanations, balancing timing versus immediacy, and transforming each story into a teachable moment.
This course teaches students how to think about research – from data collection to data analysis to reporting results – as a narrative process. Rooted in basic statistics, the course provides students who have some numeric literacy a clear and direct path for advancing from reportable results to stories with impact. Students will especially learn how to construct numeric stories that demonstrate causality.
Learning outcomes:
- Enumerate and defend the core relationships between research design and story-building, as well as define a valid causal inference and possible fallacies.
- Generate hypotheses based on data, explain how the hypotheses could be tested, and show how to translate different experimental designs and data pools into stories
This course provides key strategies to visualize results and enhance visual communication of data stories, followed by a deeper dive into how to go from analysis of results to a compelling story enhanced with visuals.
Learning outcomes:
- Create specific data visualizations that carry forward casual narratives, such as stacked bar charts, time series, and multidimensional causal chains, using effective and recognized visual and charting building blocks.
- Become familiar with how to avoid common pitfalls in designing visual content with narrative goals.
- Identify story elements that map onto the five narrative techniques learned and demonstrate through written compositions the ability to use them effectively.
In this course, students learn how to create data stories that use ethical research and protect basic human rights: autonomy, fairness, trust, beneficence, and nonmalevolence.
Learning outcomes:
- Define and use appropriate checks and reasoning processes for ensuring data transparency, validity, and ethical use.
- Identify the effect of a story by the amount of belief change it induces in an audience, determine the threshold of significance for various audiences, and use the amount and type of learning for each story to predict the degree to which it could be an actionable story or not.
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