Graphics and statistics for cardiology: comparing categorical and continuous variables
1Department of Biostatistics, University of Washington, Seattle, Washington, USA.
Heart (British Cardiac Society)
|January 29, 2016
Summary
This paper offers guidance on appropriate graph selection for data visualization in scientific manuscripts. It details various chart types for quantitative and categorical data to improve data presentation.
Area of Science:
- Biostatistics
- Data Visualization
- Scientific Communication
Background:
- Graphical data representation is essential for statistical analysis in scientific manuscripts.
- Inappropriate or poorly executed graphs often necessitate revisions, delaying publication.
Purpose of the Study:
- To provide authors with guidance on selecting and executing appropriate graphs for data presentation.
- To improve the quality of graphical data display in scientific publications.
Main Methods:
- Presentation of various graph types suitable for data commonly encountered in biomedical research (e.g., Heart).
- Inclusion of dot charts, violin plots, histograms, boxplots for quantitative data.
- Inclusion of mosaic plots and bar charts for categorical data.
Main Results:
- Demonstration of specific graphical methods for effective data representation.
- Justification of plot choices based on principles of visual perception.
- Provision of software instructions and examples using popular packages.
Conclusions:
- Properly chosen and executed graphs enhance data interpretation and statistical analysis.
- This guide aims to reduce manuscript revisions related to data visualization.
- Authors can improve the clarity and impact of their research findings through better graphical displays.
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