The Power of Visuals
Lesson 22 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
The Power of Visuals
Lesson 22 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
Lessons
Introduction
1Class Introduction
03:29 2Do The Exercises
00:37 3Communication Challenges and Solutions
05:20 4Exercise: 4X4 Model
04:31 5Exercise Solution: 4X4 Model
03:25 6Introduction - Quiz
Thinking Like a Communicator
The Power of Story
06:48 8Six Ways to Tap Into Your Inner Storyteller
12:32 9The Importance of Understanding Your Audience
03:42 10How to Understand Your Audience
04:35 11How to Embrace Emotion (to review)
04:38 12How to Tap Into Your Inherent Creativity
05:55 13Exercise: An Emotional Story
01:29 14Exercise Solution: An Emotional Story
01:12 15Thinking Like a Communicator - Quiz
Telling Data Stories
16Basic Data Analytics Tactics
08:54 17Basic Journalism Tactics
04:56 18Defining Your Story
05:37 19Sketching and Storyboarding
07:05 20Use Your Words
04:20 21Telling Data Stories - Quiz
Essential Design Principles
22The Power of Visuals
07:44 23How to Pick the Right Chart for Your Data
05:19 24Exercise: Chart Selection
06:27 25Exercise: Visualization
02:59 26Basic Chart Designs Principles
08:21 27Research Driven Design Principles
06:27 28Exercise: A Data Story
03:50 29Essential Design Principles - Quiz
And Now What?
30Great Data Stories for Your Inspiration
05:53 31Tips and Tricks
03:53 32How to Sell Data Storytelling Services
03:56 33A Conversation Guide for Talking to Prospects About Data Storytelling Projects
05:30 34Course Summary
02:48Final Quiz
35Final Quiz
Lesson Info
The Power of Visuals
in this section of the course. The focus is on the visual chart design best practices finding the best charts for your data and a couple of research findings that will help you create data stories and visuals that cut through the clutter if you've ever heard me speak before, much of this will not be new to you. But this is incredibly important and I think interesting information. All humans are visual learners, every single one of us. There are many psychological neurological and anatomical reasons for this. 70% of your sensory receptors are in your eyes, your body is wired to see things biologically. This is more important than any other sensory input. But the important part really happens in your brain of course. And did you know that fully half of your brain is devoted to visual processing? Half think about that. What's really fascinating is that we see things in certain ways. There's an entire field of psychology devoted to visual perception and it's largely based on the field of g...
estalt psychology which began to look closely at how we perceive things in the 1930s and 40s. The basic idea is that human see not just individual elements. When we see things, we don't just see a bunch of dots or lines here we see a cohesive whole, a chart. This field of psychology is actually where the constantly misquoted but well known aphorism comes from the whole is other than the sum of the parts. In other words. The idea is that we don't see just the parts, but the whole which is not necessarily more than the sum of the parts, but it is its own discrete thing. In gestalt psychology, there are a series of principles that have been identified that have a specific bearing on how we make those various parts. Some up to a whole. For our audience. For instance, the most basic is called proximity. And as you might guess, the idea is that when humans see things near each other, they perceive them as going together. So the clump of dots to the left have something to do with each other, as do the ones on the right and the two groups are distinct from each other. This isn't something we learned, this is brain science. We're wired to see things this way or there's the principle of similarity which says that when we see similar things, we group them together. So the purple dots have something to do with each other and the yellow dots have something to do with each other and the two groups are distinct from each other. You can see that sometimes both of these principles apply in this case, I can see I have proximity and similarity duking it out. But any human will see those two factors and make judgments about the visual whole based on the attributes of those parts. There are several more gestalt principles and if you read any book on data visualization or just google gestalt principles, you'll find them. But for our purposes here, I want to focus in on the most important concept in all of this, which is called pre attentive processing Gestalt principles apply to us in a pre attentive way, meaning that the moment you see a visual you're processing that information before you're even aware of it. So a chart depending on how it's designed will make an impression on you immediately. The more you can leverage important design attributes to influence that pre attentive pattern recognition in your audience, the more impactful your data stories can be. And I just introduced another critical idea which is pattern recognition. That's what data visualization is all about when presented visual information. Our brains pre attentively go right into pattern recognition mode, this is another evolutionary advantage. Humans have. We evolved to be able to spot patterns using the same visual attributes, anguished all principles that help us make sense of visual data. Think about how ancient man would find food in a sea of green leaves. Those who could spot the berries were more likely to eat and thrive and therefore pass on their genes charts allow us to see patterns in data, not to mention the outliers that buck those trends and ignore the patterns. My favorite example to explain all of this is with this image. So we see a block of numbers here. And if I were to ask you to tell me how many fours do you see in this block of numbers, what are you gonna do? You're gonna start probably in the upper left hand corner. If you're from a left to right, reading language culture and you're gonna start reading the numbers. That's text processing. And every time you come across the floor you're going to sort of write it down or try to remember the count as soon as I turn that into a visual processing exercise by actually adding some contrast. Now the four is really pop. Now it's visual processing now in a pre attentive way, you can glance and make a pretty good guess at how many floors there are and certainly within five or six seconds as opposed to 60 seconds, everyone's gonna get 100% right, That's pre attentive processing, that's what it's all about. So how does this all really play out in data visualization? It all comes down to a very limited palette of choices We can make and design to reveal the patterns and data. We can use the placement of objects like dots in a scatter plot, we can change the height or width of an object as in column or bar charts or change the orientation of a line, which will make it stand out. This brings up another interesting gestalt principle by the way called parallelism, all humans will perceive parallel lines as being related to each other. Again, this isn't learned. This is brain science. We all see that relationship. So all humans are visual and we see things a certain way. This also plays out in the real world in very important ways. For instance, the picture superiority effect describes the idea that humans have a much stronger recall of information when that information is shared via words and images as opposed to words alone. And this effect increases with age. More specifically, many studies have shown that people are much more engaged with visual content than text only content. For instance, tweets with images get twice the engagement as text only tweets, articles and images are twice as likely to be read and remembered than words alone And infographics get four times the engagement as articles and images. There's a ton more research and information I could share about this phenomenon but I think I've covered the most important bits humans are visual. We're wired and evolved to make sense of our world using visual perception. So when you're communicating you need to tell stories. Yes, but you also need to do so using visuals. And by the way, data is particularly amenable to this. My favorite example to show why is looking at an scones quartet Francis Anscombe was an english statistician who created four data sets that all share the same mean and variance of the two variables in the data sets and beyond that, the dataset also share the same correlation between the two variables as well as the same regression lines in other words on paper statistically they're nearly identical. But if you chart them suddenly you can see how dramatically different they are from each other. Without a visual analysis of this data, you would be unlikely to understand that they're different really at all, and you certainly would have a hard time describing how they're different. Data storytelling is incomplete without visual storytelling. In other words, one key component of visual data storytelling is what we call charts, although that word is too narrow. But in the next video, we'll talk about how to find the best visualization for your data, sort of
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