Regardless of the type of analysis we carry out -exploratory or predictive-, the correct visualization of the data to be analyzed, the intermediate results we generate and the conclusions we reach are a critical part of the process. Not only because of the fact that a proper understanding of the data is the first and necessary step to achieve the ultimate goal of successful analysis -an understanding that is largely based on our ability to understand the shape and nature of the data-, but because it will be our ability to transmit the information correctly to all interested parties that will determine the degree of understanding of the conclusions reached and the consistency and vigor of the measures taken from them.
In this course we will review the theory and practice involved in the correct transmission of information using data visualizations.
Content:
- Introduction
- The audience
- The context
- The objective
- Dimensions and metrics
- Type of data
- Quantitative variables
- Qualitative variables
- Temporal variables
- Geographic variables
- Relational variables
- Visual variables
- Position
- Scale
- Shape
- Size
- Brightness
- Colour
- Orientation
- Texture
- Movement
- Graphic elements
- Primitive graphics
- Types of visualizations
- Types of graphs
- Distribution graphs of a variable
- Relationship graphs of two quantitative variables
- Graphs of relationship of quantitative-qualitative variables
- Other graphics
- Report layout
- The principles of Gestalt
