BIS 140

This course helps you develop the ability to think critically about numbers, graphs, and visualizations that you encounter in news media. Data are inescapable and all kinds of folks use numbers to convince you of their ideas, but when are their arguments based on evidence and when should you doubt their claims? Through this course, you will practice unpacking numerical arguments and make your own decision about whether they are convincing and trustworthy. We’ll go through different examples and apply principles of good visualizations to assess how data are presented. This course is open to any student regardless of interest or experience, and it may even inspire you to study advanced courses about data visualization.

General education credits: RSN

Data is? Data are?

Technically speaking words like data and media are plural. That goes back to their Latin roots, and the singular versions of the words are datum and medium. But languages change, and now it’s acceptable to treat data and media as either singular or plural. Just be consistent in your own work. Examples:

• The data show an increase in student grades.
• The data shows an increase in student grades.
• The media are improving their data visualization.
• The media is improving its data visualization.

Learning Goals

By the end of this course, you will be able to:

• adopt professional courtesy, including promptly submitting assignments that you completed
• identify the types of data used to make the data visualizations that frequently appear in news media.
• interpret and evaluate claims based on visualizations, analyses, sources, and arguments of numerical data.
• compare numbers and numerical arguments reported in news media compared to primary scientific sources.
• critique of a data visualization used in journalism, including recognizing its biases.
• apply a critical lens to ethical and unethical ways to persuade the public.

Is this course for me?

I have designed this course to introduce any college student to data visualization in news media. There are no prerequisites.

Access to technology

Half of this course is online and therefore requires a reliable fast-speed Internet connection. The Open Learning Lab and the library can provide access on-campus if you need it. You also need to make sure that you know how to access the course using Canvas. If you are not familiar with Canvas, please visit the UW IT's Canvas Help for Students page. We’ll be using Microsoft Excel, Google Sheets, and some online apps to complete the statistical analyses for your research projects.

Context for this course in IAS

The School of Interdisciplinary Arts and Sciences focuses all students’ experiences around five core learning objectives: These objectives apply across all areas of study and your experiences in every IAS course should allow you to develop your abilities and understanding in most, if not all, of the five objectives. The material and assignments in this course will help you in these topics.

• Collaboration and shared leadership. You’ll share some of your assignments within your groups to learn from them and to share what you’ve learned with them. You’ll also help each other understand the readings.
• Critical thinking. You will evaluate different numerical representations in the news, and develop your own.
• Diversity and equity. You will study the bias generated through different data visualization schemes and brainstorm ways to minimize that bias.
• Interdisciplinary research and inquiry. You will see how many different fields rely on numerical thinking to reach and communicate conclusions
• Writing and presentation. You will focus on evaluating and presenting different ways of understanding numbers.

These objectives apply across all areas of study and your experiences in every IAS course should allow you to develop your abilities and understanding in most, if not all, of the objectives.

Textbook

All readings and videos will be available through the course website, including the textbook. The textbook is: Schwabish, J. 2021. Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks. Columbia University Press. Stable URL.