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Unit Overview
Unit Overview
You've crunched the numbers and suffered through statistics. Now it's time to turn the data insights you discovered into visualizations that summarize the trends you observed. Data visualization is a powerful, engaging method of communicating research results. The way data are represented can have persuasive impacts on public audiences. As consumers and producers of data, it's important that we recognize data misrepresentations, or data that is being displayed in a misleading matter, and that - in our own production of data communications - we maintain high ethical standards concerning the clarity and accuracy of our visualizations. To do this, you'll need to get clear on the purpose of your data communication, as well as the intended audience for your communication. Additionally, we'll review some basic guidelines for creating accessible data visualizations, including which types of visualizations are appropriate for your data.
Key Terms
Key Terms
Audience: the intended viewers of your data visualization, who will use the information you communicate for a specific purpose.
Color palette: a color scheme used in a data visualization.
Data misrepresentations: distortions in data visualizations that lead to inaccurate conclusions, often for persuasive purposes.
Data visualization: an accessible way to understand data by representing trends and patterns in graphics.
Readability: the ease with which a reader can interpret a text or visualization.
Why Visualize Data?
Why Visualize Data?
Data skills are increasingly desirable in professional and corporate employment settings, as a growing number of fields recognize the power of drawing on data to highlight performance trends, analyze market dynamics and consumer behaviors, and design communication strategies. Professionals in the 21st Century need to be able to leverage data to tell engaging, informative stories that make complex data accessible to a wide range of audiences. Learn more about the growing interest in data communication in the video and article at right.
Basic Visualization Principles
Basic Visualization Principles
Knowing some basic rules of thumb for creating data visualizations that are highly readable, or easy to understand by diverse audiences, will help you communicate the important and interesting information you learned in your data analysis. See the presentation at left for more information about data visualization basics.
Food for Thought
Food for Thought
The National Institutes of Health estimate that 1 in 12 men experience a version of color blindness that distorts their view of certain hues (NIH 2019). Learn more about selecting smart color schemes that can be understood by all audiences in this article from Chartio.
Creating Data Visualizations
Creating Data Visualizations
Making effective data visualizations requires attention to detail and a healthy dose of creativity. Follow the instructions in the slide presentation to generate data visualizations that you will incorporate in a research brief.
You will be prompted to use two web resources as you create your graphics. Use the navigation buttons below to access Canva and the Adobe Color website.
Summary
Summary
Communicating your data through informative and engaging visualizations is an important skill applicable to a wide range of settings. Data visualizations provide a summary of important findings that, when created effectively, can be quickly and easily understood by your audience. As they say, "A picture's worth a thousand words!" That makes data visualization a powerful communication tool that must be utilized accurately and ethically.
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