The pits and falls of graphical presentation

Area of Science:

• Scientific communication
• Data visualization
• Research methodology

Background:

• Graphics are essential for interpreting research data.
• Poorly chosen graphics can obscure results or introduce distortions.
• Existing resources often focus on "good" vs. "bad" graphics, lacking practical guidance.

Purpose of the Study:

• To provide guidelines for effective graphic presentation of research results.
• To offer novel examples for visualizing basic and complex data types.
• To inspire researchers in creating their own data visualizations, particularly for multivariate models.

Main Methods:

• The paper presents a set of guidelines for creating research graphics.
• It includes uncommon examples for visualizing diverse data types.
• Focuses on methods to present multivariate model results effectively, often replacing tables.

Main Results:

• Guidelines for selecting appropriate data and graphic types are provided.
• Uncommon visualization examples are presented for basic and complex data.
• Methods for visualizing multivariate data beyond tables are suggested.

Conclusions:

• Researchers should carefully consider data and graphic choices for clarity.
• Novel visualization techniques can enhance understanding of complex data.
• The paper aims to inspire innovative approaches to scientific graphics.