Data visualization is an important part of statistics. A good graph enables you to spot trends and relationships you might otherwise miss if you look only at numbers. Graphics are valuable for another reason: They help you present your ideas to groups.
This is especially important in the field of data science. Organizations rely on data scientists to make sense of huge amounts of data so that decision-makers can formulate strategy. Graphics enable data scientists to explain patterns in the data to managers and to nontechnical personnel.
Finding Patterns
Data often resides in long, complex tables. Often, you have to visualize only a portion of the table to find a pattern or a trend. A good example is the Cars93 data frame, which resides in the MASS package. (In Chapter 2, I show you how to put this package into your R library.) This data frame holds data on 27 variables for 93 car models that were available in 1993.
Figure 3-1 shows part of the data frame in the Data Editor window that opens after you type
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Using graphs to find patterns