“Now You See It” is data visualization expert Stephen Few’s new book, explaining how to use simple visual techniques for quantitative analysis. In this textbook-sized offering, Stephen explores one of the more overlooked aspects of analysis: the graphic representation of information.
Stephen lays the foundation for good visual analysis in Part I by defining how we perceive information. He states, "…there are ways to visually display data that are effective because they correspond naturally to the working of vision and cognition, and there are ways that break the rules and consequently don’t work. If we wish to display information in a way that will enable us and others to make sense of it, we must understand and follow the rules.”
He goes on to explain that we "…perceive several basic attributes of visual images pre-attentively, that is, prior to and without the need for conscious perception."
Below is a list of those pre-attentive attributes that are quantitatively perceived in and of themselves, without having values arbitrarily assigned to them:
Length – longer =greater
2-D Position – offset higher/lower, or left/right=greater
Width – Wider=greater
Size – Bigger=greater
Intensity – Darker=greater
Blur – Clearer=greater
These pre-attentive attributes help us all consume and digest information and make sense of their meaning. However, Stephen points out that "pre-attentive symbols become less distinct as the variety of distracters increases. It is easy to spot a single hawk in a sky full of pigeons, but if the sky contains a greater variety of birds, the hawk will be more difficult to see."
Good visualizations not only take advantage of the pre-attentive attributes mentioned above, but they also use them appropriately while considering the limitations of our visual memory.
Stephen explains that we have both "working memory and long-term memory. Working memory stores information only briefly. Working memory is where information resides when we are thinking about it. If we think about it long enough, it will end up in long-term memory."
And visual memory (which is part of working memory) is very limited. Visual memory processes information in “chunks.” How much is a chunk of information? Well, it depends on how it is conveyed. Information chunks have to be relatively small when they consist of text or numbers. However, they can be larger when served up graphically.
Part II, which is the meat of the book, takes the reader through several different analyses and shows examples of good visual techniques to best convey the information used in each one.
Part III covers promising new trends. Here, Stephen discusses “Illuminating Predictive Models,” and this is where JMP is prominently featured.
Noting that his book largely focuses on analysis of existing information, or descriptive statistics, here he highlights the benefits of predictive statistics. "If we understand the past well enough to describe it clearly and accurately, we can often build a model that we can use to predict what will likely happen as a result of particular conditions, events, or decisions in the future," Stephen writes.
He explains that "the goal of predictive analysis is not to produce certainty about the future, but to reduce uncertainty to a degree that enables us to make better decisions.“
He then describes what he refers to as “transparent predictive models.” And it is here where Stephen uses JMP to explain how transparent predictive models help us make better decisions with less risk. He says, “This level of involvement in the analytical process [using transparent predictive models] takes advantage of our brains in a way that throws open the windows to insights that we might never otherwise experience.”
Many of the visualizations discussed in Stephen’s book are available in JMP. But even more importantly, JMP’s visualizations also incorporate world-class analytics. This is why, when Stephen turns his attention to more advanced analytics, like predictive modeling, JMP is prominently featured.
“Now You See It” is a must-read for anyone who needs to explore and understand data that guides his or her decision-making process. Following Stephen’s advice will help readers explore their data better, discover trends and patterns more quickly, and make decisions with confidence.