For this assignment, you will have three deliverables:
1. A summary of your data
2. Two visualizations of your data
3. Justification for the type of visualizations you chose
Part I – Data Summary:
Summarize your data through basic or detailed numeric summaries and through a characterization done by looking at any or all of the following:
Distribution
Skewness
Kurtosis
Missing values in data sets
As part of your summary, describe how the statistics generated may be valuable in determining potential areas of investigation.
Part II – Visualizations:
Choose two different visualizations using any of the methods learned in Section 5.1. You must provide two visualizations (by screenshots) of the data set you chose in Module Two.
Part III – Justification of Visualizations:
From Data Mining With R and Rattle: The Art of Excavating Data for Knowledge (p. 99):
Through exploring our data, we can discover what the data looks like, its boundaries (the minimum and maximum values), its numeric characteristics (the average value), and how it is distributed (how spread out the data is).
The data begins to tell us a story, and we need to build and understand that story for ourselves .
By capturing that story, we can communicate it back to our clients.
Justify the rationale for selecting one or more of these visualizations to tell a “story.” What aspects of the visualization are uniquely suited to the use of this method?
