Exploratory Data Analysis ( EDA ) is the process of organizing, plotting and summarizing a data set. EDA was developed by one the greatest statistician of all time John W. Tukey. In his book “Exploratory data analysis” in 1977 where the principal for EDA was laid. He said “Exploratory Data Analysis can never be the whole story, but nothing else can serve as the foundation stone.”

“Exploratory Data Analysis can never be the whole story, but nothing else can serve as the foundation stone.” – John Tukey

The objective of EDA are to:

• Suggest hypotheses about the causes of observed phenomena.
• Assess assumptions on which statistical inference will be based.
• Support the selection of appropriate statistical tools and techniques
• Provide a basis for further data collection through surveys or experiment

Techniques used in EDA

• Graphical Techniques
• Dimentionality Reduction
• Quantitative Techniques

Some of the graphical techniques used in EDA are:

• Box Plot
• Histogram
• Multi-vari chart
• Run chart
• Pareto chart
• Scatter plot
• Stem-and-leaf plot
• Parrel Coordinates

Some of the Dimentional Reduction techniques in EDA are:

• Multidimensional scaling
• Principal Component Analysis (PCA)
• Multilinear PCA
• Nonlinear dimensionality reduction(NLDR)

Some quantitative techniques are:

• Median polish
• Trimean
• Ordination

Note: Some of the information is extracted from wikipedia