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Chapter 4 Exploratory Data Analysis

Chapter 4 Exploratory data AnalysisA first look at the mentioned in Chapter 1, Exploratory data Analysis or EDA is a criticalfirst step in analyzing the data from an experiment. Here are the main reasons weuse EDA: detection of mistakes checking of assumptions preliminary selection of appropriate models determining relationships among the explanatory variables, and assessing the direction and rough size of relationships between explanatoryand outcome speaking, any method of looking at data that does not include formalstatistical modeling and inference falls under the term Exploratory data Typical data format and the types of EDAThe data from an experiment are generally collected into a rectangular array ( ,spreadsheet or database)

determining relationships among the explanatory variables, and ... of the areas of a distribution that would commonly occur. This can also be thought of as sample data values which correspond to areas of the population pdf (or pmf) with low density (or probability). The de nition of \outlier" for standard boxplots is described below (see4.3.3). ...

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