根据统计学家的可视化:关于可视化在推理统计学中的作用的采访研究
IEEE transactions on visualization and computer graphics
|October 23, 2023
概括
专业统计学家在整个工作流程中大量使用数据可视化,经常依赖视觉模型进行统计推断. 他们的见解表明,改进的视觉显示可以更好地表示统计不确定性和效果大小.
科学领域:
- 统计 统计 统计 统计
- 数据可视化 数据可视化
- 人与计算机的交互
背景情况:
- 数据可视化是统计分析的组成部分.
- 了解统计学家对视觉效果的使用,可以为创造意义的最佳实践提供信息.
- 很少有研究探讨统计学家如何在心理上建模和视觉上表示统计推理.
研究的目的:
- 调查统计学家在分析过程中如何利用数据可视化.
- 探索统计学家对推断统计方法的心理模型.
- 收集统计学家的设计建议,用于可视化统计推理.
主要方法:
- 采访了18名专业统计学家 (平均经验为19.7年).
- 诱导参与者生成的视觉设计用于统计推理.
- 使用专题分析和开放编码分析了采访成绩单.
主要成果:
- 统计学家在所有分析阶段都使用可视化,而不仅仅是用于报告.
- 推理统计的心理模型主要是视觉的.
- 许多统计学家更喜欢细微的表示,而不是二分法 (例如,显著/非显著) 的结果.
结论:
- 可视化是统计学家在整个分析工作流程中的关键工具.
- 基于视觉的心理模型突出了改善统计表示的机会.
- 结合效果大小和不确定性的多面视觉显示可以增强统计推理通信.
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