A data analyst is given a new dataset and is in the initial phase of analysis. The analyst's first steps are to understand the data's main characteristics by creating summary statistics, plotting histograms to see the data's shape, and looking for outliers. Which analysis technique is the analyst using?
This approach, known as exploratory data analysis (EDA), evaluates raw data at an early stage. It uses charts, summary measures, and simple transformations to highlight important observations and guide further investigation. Other techniques like performance analysis focus on tracking against goals, trend analysis focuses on time-based comparisons, and link analysis focuses on relationships between data points, but EDA emphasizes the initial evaluation of the dataset.
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What is Exploratory Data Analysis (EDA)?
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Why are visualizations important in Exploratory Data Analysis?
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What types of unusual data points can EDA identify?