[MUSIC]. 
In this lecture we're going to go through 
the step by step process of how to 
evaluate a visualzation. 
The first step is to consider the purpose 
of the visualization and who the intended 
audience is. 
In other words, is it to educate, to 
inform, or is it for exploration? 
Is the audience the general public, or a 
specialized body of scientists, for 
example? 
That's very important in deciding what 
the overall value is of this particular 
type of visualization. 
Don't make the mistake of judging a 
visualization without understanding the 
intended audience. 
Next determine your initial reaction. 
Is it generally positive or negative? 
It's all right to have an emotional 
reaction to a visualization, but also try 
to step back and analyze it somewhat 
dispassionately. 
Examine the visualization in detail. 
What works well, what doesn't. 
And finally answer questions such as the 
following. 
Is the design aesthetically pleasing? 
Is it immediately understandable? 
If not, is it understandable after a 
short period of the study. 
Does it provide insight or understanding 
that was not obtainable with the original 
representation text or table, etcetera. 
This is very important. 
If the only difference between the 
visualization is that somebody added 
color to the design and made a pie chart 
out of it, that does not necessarily make 
it valueable. 
A visualization should add value over a 
textual representation or it is not a 
good visualization. 
Fourth, does it provide insight or 
understanding better than some 
alternative visualization would, or does 
it require excessive cognitive effort? 
What kind of visualization might have 
been better? 
For example, if somebody has given you a 
set of multiple pie charts, and you have 
to compare pie wedges from one to the 
other. 
Is that really the best way to make those 
comparisons? 
Or could a bar chart have done the job 
just as well? 
Maybe better. 
Does the visualization reveal trends, 
patterns, gaps, or outliers? 
Can the viewer make effective 
comparisons? 
Does the visualization successfully 
highlight important information while 
providing context for that information? 
Is new information gleaned from the 
visualization that wouldn't have come 
from an alternative method? 
And is the important information 
highlighted? 
And is the context not hidden? 
Number seven, does it distort the 
information? 
If it transforms it in some ways, this 
misleading, or hopefully simplifying. 
Does it omit important information? 
Is it memorable? 
Does it use visual components properly? 
That is, does it represent the data using 
lines, color, position, etcetera, as we 
discussed in earlier lectures? 
Does it transform nominal, interval, and 
quantitative information properly? 
And does it use labels and legends 
appropriately?