🕶 The Nature of Data

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Where does Data come from?

Let us look at the slides.

Why Describe and Graph Data?

Summaries are compressed data
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.
Business Data Viz includes shapes that carry strong cultural and business 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/

What are Data Types??

https://www.youtube.com/watch?v=dwFsRZv4oHA

In more detail:

How do we Spot Data Variable Types?

By asking questions!

Pronoun	Answer	Variable / Scale	Example	What Operations?
What, Who, Where, Whom, Which	Name, Place, Animal, Thing	Qualitative / Nominal	Name	Count no. of cases Mode
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	Socio -economic status (“low income, middle income, high income) education level (“high school”, “B S”,” M S”,“PhD”) income level (“less than 50K”, “50K-100K”, “over 100K”) Satisfaction rating ( “extremely dislike”, “dislike”, “neutral”, “like”, “extremely like”).	Median Percentiles
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). Year of Starting in College	Mean Standard Deviation
How Many / Much / Heavy? Few? Seldom? Often? When?	Quantities, with Scale and a Zero Value. Differences and Ratios /Products are meaningful. (e.g Weight )	Quantitative / Ratio**	Weight,length,Height Temperature in Kelvin Enzyme activity, dose amount, reaction rate, flow rate,concentration Pulse Survival time	Correlation Coeff of Variation

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.

References and Reading

Datasets Have Worldviews,https://pair.withgoogle.com/explorables/dataset-worldviews/