My Work Showcase
In statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.
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Intro to EDA
content
Exploratory Data Analysis
detecting patterns
finding outliers
making comparisons
identifying clusters
Our Goal: Data Insight
Either for us, as data analysts, or for an audience Not all data visualizations produce insights Some are beautiful
Some misinform (deliberately or not)
Focus should be on the data, not the tool
How do we gain insight?
Deep understanding of the dataset, where it came from, what its limitations
Experiment with different graphic forms, based on theory on what forms work well with different data types
"Exploratory data analysis can never be the whole story, but nothing else can serve as the foundation stone--as the first step."
Tukey 1977
"Visualization is critical to data analysis. It provides a front line of attack, revealing intricate structure in data that cannot be absorbed in any other way. We discover unimagined effects, and we challenge imagined ones."