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Statistical software has become quite sophisticated in giving users high-quality graphs with ease. Still, a few customization steps can improve a graphical representation. The goal of customization is to produce more effective graphs. What are some useful guidelines on constructing a graph? A good graph is self-contained. This means that everything on the graph should be explained:
All the axes should be labeled in understandable terms.
Marker symbols should be clearly identified.
Smoother lines and connecting lines should be recognizable throughout the range of the graph.
Marker symbols identifying subgroups of data should clearly differentiate between subgroups.
Axes scales and tick spacing should facilitate comparisons with other graphs.
Annotations on the graph should be helpful for interpretation. Unhelpful annotations, sometimes referred to as chart junk, should be avoided.