Prior to performing any type of statistical analysis, understanding the nature of the data being analyzed is essential. You can use EDA to identify the properties of a dataset to determine the most appropriate statistical methods to apply to the data. You can investigate several types of properties with EDA techniques, including the following:
The center of the data
The spread among the members of the data
The skewness of the data
The probability distribution the data follows
The correlation among the elements in the dataset
Whether or not the parameters of the data are constant over time
The presence of outliers in the data
Another key question EDA answers is "Does the data conform to our assumptions?" Identifying the properties of a dataset is very important, because many statistical procedures are sensitive to the assumptions you make about the data.