探索性数据分析 [Exploratory data analysis]

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定义: 探索性数据分析（exploratory data analysis，简称EDA）是一种成熟的统计传统，为揭示数据中的模式提供了概念和计算工具，以推动假设的发展与完善。这些方法补充了验证性数据分析（confirmatory data analysis，简称CDA）的假设检验。即便在有明确理论支撑的情况下，EDA 仍能帮助解释CDA发现的结果，并揭示数据中意外或误导性的模式。

相关术语: Confirmatory analyses, Data-driven research, Exploratory research

参考文献:

  • Behrens, J. T. (1997). Principles and procedures of exploratory data analysis. Psychological Methods, 2(2), 131–160. https://doi.org/10.1037/1082-989X.2.2.131
  • Box, G. E. P. (1976). Science and statistics. Journal of the American Statistical Association, 71(356), 791–799.
  • Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley.
  • Wagenmakers, E. J., Wetzels, R., Borsboom, D., van der Maas, H. L., & Kievit, R. A. (2012). An agenda for purely confirmatory research. Perspectives on Psychological Science, 7(6), 632–638. https://doi.org/10.1177/1745691612463078

原稿作者: Jenny Terry

审阅者: Helena Hartmann, Timo Roettger, Charlotte R. Pennington, Flávio Azevedo

翻译者: AI-driven translation tool "TransFlow" (developed by Jinbiao Yang and COSN OpenTransfer team)

译稿审阅者: Xuejun Ryan Ji, Liangjie Chen, Ruoting Liu, Shuxian Jin