Messages in Data

Karl Ho

School of Economic, Political and Policy Sciences

University of Texas at Dallas

Data Visualization

Data Story:

Data

Message

Mechanical process

 Data                  Messenger             Message     

>                                              >

=                                             =

Visualizing Numbers

  1. Learn from Journalism

    1. What can impress readers?

      1. Data, very good data

      2. Emotions

      3. Art, entertaining, beautiful art

  2. Learn from the best

    1. Hans Rosling

    2. Edward Tufte

    3. William Cleveland

    4. Leland Wilkinson

What to Visualize?

What do you read from this chart?

  • Patterns
  • Trends
  • Questions (puzzling data)

Numbers

  1. Numbers vs. ?

  2. Zeros and ones

  3. Integers (0, 1, 2, 100) vs.
    Non-integers (2.5, 3.1416) 

  4. Positive and negative numbers

Quantitative vs. Qualitative Data

  1. Numbers vs. Labels

  2. Quantity vs. Quality

  3. Ordinal, Interval, Ratio vs. Nominal

  4. e.g. Yes/No--> Qualitative

  5. e.g. How much--> Quantitative

Quantitative vs. Qualitative Data

  1. Higher quantity means higher quality?

  2. Higher quality leads to higher quantity?

Basics of data organization

  1. Variables and observations

    1. Alternative terms: Attributes, Features, Fields and cases

  2. Rows for observations , columns for variables

  3. Names and labels

  4. Table vs. query

What to visualize in data?

  1. Data Generating Process

  2. Property

  3. Distribution

  4. Pattern

  5. Differences

  6. Relationship

  7. Dimensionality

Time series data

  1. Nature

    1. Temporal dependency: non-stationarity autocorrelation

    2. Periodicity: seasonality, cycle

  2. Zeros -> events?

  3. Scale linearity

Event count data

  1. Nature

    1. Distribution

    2. Bounds

      1. No upper bounds

      2. One lower bound: zero

    3. Zeros

  2. Continuous vs. discrete

  3. Intervals vs. duration

Bertram M. Gross (1986)

"the world or my part of it is seen as an ongoing stream of events in time . . . Facts and process are separated into discrete elements only by human analysis . . . Change-whether rapid or slow, hidden or open-is continuous."

Anscombe example (1973)

Anscombe example (1973)

Anscombe example (1973)

Anscombe example (1973)

Anscombe example (1973)

Tufte: Same relationship? (2001)

Tufte: Same relationship? (2001)

Jan Vanhove example (2016)

Jan Vanhove example (2016)

Elements of a Chart

  1. Dimensionality

    1. How many dimensions are there?

  2. Relationships

    1. ​Strength

    2. Fit

    3. Error bands

    4. Panels