What role does EDA play in formulating hypothesis or model selection in data analysis?
- All of the mentioned
- It assists in defining the variables to be used in the model
- It enables an understanding of the relationships among the variables
- It helps in determining the type of model to apply
EDA plays a fundamental role in hypothesis formulation and model selection. It can guide the choice of the most suitable models based on the understanding of data structure and relationships between variables. It helps define the variables to use in the model, identify potential outliers, detect multicollinearity, and assess the need for variable transformation or creation. Therefore, EDA forms the foundation for further statistical or machine learning analysis.
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