Module #7 Assignment: Visualizing Distributions in R

 


Dataset Used:

This visualization uses the classic mtcars dataset that was also the class dataset for Module # 7. This includes mpg, cylinder count, horsepower and weight data for 32 car models. In this visualization we plotted fuel economy by cylinder count (4, 6, and 8).

Patterns Revealed:

The histogram showed different fuel efficiency curves by cylinder count. And the 4 cylinder cars had the best mpg figures - roughly 22 to 34 mpg. 6-cylinder cars scored moderate fuel efficiency at 17 to 21 mpg. But the 8-cylinder cars got between 10 and 19 mpg -- the most fuel -- instead. The obvious difference in distributions reveals that larger engines are better but less efficient.

Alignment with Few & Yau's Recommendations:

This design follows Stephen Few and Nathan Yau's advice for honest data visualization. Aligned x-axes with constant bin width across the three cylinder groups allow direct visual comparison of their distributions. Grey with dashed median lines and no non-data ink means only reference points are visible - following Few's rule of simplicity & focus. Similarly, Yau wants the context of labeled axes, a title and a bin width caption. All these design choices help viewers decipher the data quickly and easily without fuss.

Reflection on Few's Critique: 

Distributions are misleading or too decorative and obscure rather than show the patterns, which is what Few points out. In many dashboards / reports, inconsistent scales / flashy colors skew the data a bit. As with Few's minimalist visualization and Yau's context-based comparability approach, this one avoids those pitfalls by focusing on the data itself - how fuel efficiency decreases with engine size.

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