The world will believe what you want it to believe - an adage hinting on how perception is really important. This philosophy percolates to data, visualization, and analyses. Only things that can be perceived can be interpreted. In that, data visualization and graphical perception are the strongest tool to interpret data. Also, an important point is to present the data that closely aligns to human perception and the way neurons/cognitive brain transmits information - what humans can see, believe, and interpret. Cleveland and McGill have strongly concluded the strong correlation between perception and interpretation, resulting in better judgment and decision making.
Also the authors conduct experiments where the graphics with perceptual tasks trumps a heap of quantitative representation of the same information (in terms of decision making/judgment or predicting patterns and behavior). They have several other findings where the positions are more accurate than lengths/angles, leading to discoveries of divided bar and pie charts that are more informative than the archaic ones. Lack of proper judgment leads to statistical miscalculations, resulting in wrong quantification and interpretation. Hence, the authors prove the significance of graphical perception, representation and the evolved way of measuring and using the right approaches.
In fact, perception and visualization have significant role in behavioral economics as well - a subject so qualitative that it is hard to come to a logical conclusions on the interpretations. Dan Ariely, Professor of Psychology and Behavioral Economics at Duke University and author of Predictably Irrational uses perceptions and behaviors to disprove some of the basic statistical concepts. For example, a simple supply/demand relationship defies the logic of the demand curve when the prize of goods fall to ‘Zero’ and the compounding effect it has on the demand, only based on how humans perceive the number Zero, visually, in their neo-cortex/hypothalamus. The demand for goods at prize zero is irrationally higher than the demand at $0.1. Shouldn’t the demand at $0.1 be linear and almost as high as it was at $0? If yes, why do people flock to stores when there are free giveaways and not purchase the same items if sold for $0.1? (Let us say a candy discounted from $5 to $0.1 as opposed to $5 to free - research stating a significant drop in demand at $0.1 that even the demand curve can’t explain). Time and again, it is proven that perceptions matter a lot, and has significant importance in data interpretation. Hence, graphical perception will hold its forte in the years to come, evolving, but still closely tied to the fact that aligning to human perceptions give the best interpretation.