Data Analysis and Visualization
Business Finance
Exploration: Use a tool of your choice (common recommendations would be Excel, Tableau, R) to visually explore the two datasets separately in order to deepen your appreciation of their physical properties and their discoverable qualities (insights) to help you cement your understanding of their respective value.
1. Make the data stand out. The focus here is on revealing the structure of the data. It includes discussion of how to fill the data region, transform data, choose an appropriate scale for an axis, eliminate chart junk and other superfluous material, and avoid having graph elements interfere with data, which includes topics such as over plotting, jittering, and transparency.
2. Add information. In addition to the usual conveyance of the importance of labeling axes and using legends, we also discuss how to: use color and plotting symbols to convey additional information; add context with reference markers and labels; and write comprehensive captions that are self-contained, describe the important features, and summarize the conclusions drawn from the graph.
3. Key Questions and Interpretations of Data Analysis…
