Pennsylvania State University 3 credits GD
The world is awash with complex, dynamic information. With the development of powerful technologies capturing vast amounts of data, the art of visually representing information in ways that increase understanding of complex data and models will become a critical skill. Effective representations can communicate information in ways that maximize comprehension, analysis, exploration, and understanding of the underlying data. Knowing how to read and interpret visual data is essential to navigating this ocean of information. Those who know how to present data visually employ a powerful communication tool. In this class, you will become an effective reader and creator of visual representations of data. Through critical assessment of examples, interactions with peers, and the generation of your own projects, you will generate visualizations of data and create works using a common visual language to help people analyze and understand the information at hand. Good visualizations not only present a visual interpretation of data, but also do so by improving comprehension, communication, and decision-making. Effectively functional visualizations can offer insights that reveal evidence and truths that may be difficult to otherwise observe. They can often empower readers to explore both the norms that give meaning to the data and the exceptions that convey its complexity or uncertainty. Visualized information can assist in revealing: - Distributions and frequency over time - Changes and trends - Relationships and correlations - Spatial and mapping information Regardless of your major field of study, the ability to effectively visualize information represents a significant and essential skill for effective communication. Whether you are creating representation of your work for your company's leadership board, a general public audience, or a meeting of your peers, the ability to craft a visual display that offers an accurate and insightful interpretation of data is a key capability in the workplace. No prior experience in design or statistics is required for success in this course.
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