Explanatory Data Analysis : course and exercises
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Date
2025
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Université Badji Mokhtar Annaba
Abstract
Exploratory Data Analysis (EDA) is a crucial component of modern statistical practice, originally articulated by John W. Tukey in 1977. It emphasizes the importance of understanding data through visualization, summary, and pattern recognition prior to formal modeling. EDA serves as a foundational tool across various scientific and industrial domains, facilitating the extraction of meaningful insights from complex datasets. This handbook targets third-year undergraduate students in Applied Mathematics, providing a rigorous mathematical foundation while emphasizing practical interpretation and active learning. It progresses from univariate to multivariate analysis, integrating theoretical concepts with real-world applications. The structured approach encompasses essential topics such as descriptive statistics, dimensionality reduction, and multivariate analysis techniques. Ultimately, this text aims to cultivate an analytical mindset, preparing students for advanced studies and professional endeavors in data analysis, echoing Tukey's belief in the value of revealing the unexpected through EDA.
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Keywords
data visualization; descriptive statistics; corrélation analysis