Chapter 4 Exploratory Data Analysis - CMU Statistics

← Back to document page

Chapter 4Exploratory 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), most commonly with one row per experimental subject6162CHAPTER 4. Exploratory data ANALYSISand one column for each subject identifier, outcome variable, and explanatoryvariable. Each column contains the numeric values for a particular quantitativevariable or the levels for a categorical variable.

Chapter 4 Exploratory Data Analysis A rst look at the data. As mentioned in Chapter 1, exploratory data analysis or \EDA" is a critical rst step in analyzing the data from an experiment. Here are the main reasons we use EDA: detection of mistakes checking of assumptions preliminary selection of appropriate models

  Analysis, Data, Chapter, Exploratory, Chapter 4 exploratory data analysis