Lab-1: What is the use of a book with no pictures?
Science, Human Experience, Experiments, and Data
Image credit: Pinterest
Where does Data come from?
Let us look at the slides. Click on the slides icon above.
Why Visualize?
- We can digest information more easily when it is pictorial
- Our Working
Memories
are both short-term and limited in capacity. So a picture
abstracts the details and presents us with an overall summary, an
insight, or a story that is both easy to recall and easy on
retention.
- Data Viz includes shapes that carry strong cultural memories and impressions for us. These cultural memories help us to use data viz in a universal way to appeal to a wide variety of audiences. (Do humans have a gene for geometry?)
- It helps sift facts and mere statements: for example:
Figure 1: Source https://www.deccanherald.com/national/india-is-known-as-the-rape-capital-of-the-world-rahul-783495.html
Figure 2: Source https://datareveals.org/crime-data/
How do we Spot Data Variable Types?
By asking questions!
| Pronoun | Answer | Variable/Scale | Example | What Operations? |
|---|---|---|---|---|
| How Many / Much / Heavy? Few? Seldom? Often? When? | Quantities, with Scale and a Zero Value.Differences and Ratios /Products are meaningful. | Quantitative/Ratio | Length,Height,Temperature in Kelvin,Activity,Dose Amount,Reaction Rate,Flow Rate,Concentration,Pulse,Survival Rate | Correlation |
| How Many / Much / Heavy? Few? Seldom? Often? When? | Quantities with Scale. Differences are meaningful, but not products or ratios | Quantitative/Interval | pH,SAT score(200-800),Credit score(300-850),SAT score(200-800),Year of Starting College | Mean,Standard Deviation |
| How, What Kind, What Sort | A Manner / Method, Type or Attribute from a list, with list items in some ” order” ( e.g. good, better, improved, best..) | Qualitative/Ordinal | Socioeconomic status (Low income, Middle income, High income),Education level (HighSchool, BS, MS, PhD),Satisfaction rating(Very much Dislike, Dislike, Neutral, Like, Very Much Like) | Median,Percentile |
| What, Who, Where, Whom, Which | Name, Place, Animal, Thing | Qualitative/Nominal | Name | Count no. of cases,Mode |
As you go from Qualitative to Quantitative data types in the table,
I hope you can detect a movement from fuzzy groups/categories to more
and more crystallized numbers. Each variable/scale can be subjected to
the operations of the previous group.
In the words of S.S.Stevens:
the basic operations needed to create each type of scale is cumulative: to an operation listed opposite a particular scale must be added all those operations preceding it.
What Are the Parts of a Data Viz?
How to pick a Data Viz?
Most Data Visualizations use one or more of the following geometric attributes or aesthetics. These geometric aesthetics are used to represent qualitative or quantitative variables from your data.
Figure 3: From Claus Wilke, Fundamentals of Data Visualization
What does that mean? We can think of simple visualizations as combinations of these aesthetics. Some examples:
| Aesthetic #1 | Aesthetic #2 | Shape | Chart Picture |
|---|---|---|---|
| Position X = Quant Variable | Position Y = Quant Variable | Points/Circles with Fixed Size |  |
| Position X = Qual Variable | Position Y = Count of Qual var) | Columns |  |
| Position X = Qual Variable | Position Y = Qual Variable | Rectangles, with area proportional to joint(X,Y) count | |
| Position X = Qu alitative Variable | Position Y = Rank Ordered Quant Variable | Box + Whisker, Box length proportional to Inter-Quartile Range, whisker-length proportional to upper and lower quartile resp. |  |
| Position X = Quant Variable | Postion Y = Quant V ariable + Qual Var |  |
|
| Quant Variable | Shape = Line with Quant Variable |  |
Arvind V.
Faculty Member, SMI, MAHE
This course will give Art and Design students a foundation in the principles and practice of data visualization using R.