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Course Description

The value proposition of data analysis is often found in the visual or story revealed from the data. Effective data analyses are stories that engage the audience and, at their best, lead the audience to a specified conclusion or insight. Often times, this means that the end result of the data analytics pipeline is not simply a graph, no matter how dynamic or attractive it may be. This class will detail the various methods and technologies for the display of quantitative information. It will push the student to go further and understand the situated-ness of the data within the organization and the relevant questions that the organization and management face. In addition, students will be introduced to the basic mechanics of machine learning and best practices for data management and handling.

Course Objectives

Upon successful completion of the course, students will be able to:

• Interpret graphical summaries for various data sets

• Critique visualizations and explain why various components do or do not work effectively in conveying a particular message

• Visualize data with both static and dynamic outputs

• Tell a story using data

• Describe the difference between machine learning and statistical hypothesis testing

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