Exploratory Data Analysis
Brian D. Haig
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Chapter 2 is concerned with modern data analysis. It focuses primarily on the nature, role, and importance of exploratory data analysis, although it gives some attention to computer-intensive resampling methods. Exploratory data analysis is a process in which data are examined to reveal potential patterns of interest. However, the use of traditional confirmatory methods in data analysis remains the dominant practice. Different perspectives on data analysis, as they are shaped by four different accounts of scientific method, are provided. A brief discussion of John Tukey’s philosophy of teaching data analysis is presented. The chapter does not consider the more recent exploratory data analytic developments, such as the practice of statistical modeling, the employment of data-mining techniques, and more flexible resampling methods.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
计算机 / AIStatistical Methods and Applications
Data Visualization and Analytics · Statistics Education and Methodologies
参考文献 0
引用本文 12
按被引量排序,此处列出前 3 条