Difference between revisions of "Exploratory Data Analysis (EDA)"
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| − | ''' | + | == What is Exploratory Data Analysis (EDA)? == |
| + | '''Exploratory Data Analysis''' refers to the critical process of performing initial investigations on data so as to discover patterns, spot anomalies, test hypotheses and check assumptions with the help of summary statistics and graphical representations. The objectives of EDA are to: | ||
| + | *Enable unexpected discoveries in the data | ||
| + | *Suggest hypotheses about the causes of observed phenomena | ||
| + | *Assess assumptions on which statistical inference will be based | ||
| + | *Support the selection of appropriate statistical tools and techniques | ||
| + | *Provide a basis for further data collection through surveys or experiments | ||
| + | Many EDA techniques have been adopted in [[Data Mining|data mining]]. They are also being taught to young students as a way to introduce them to statistical thinking. | ||
Revision as of 15:33, 15 March 2023
What is Exploratory Data Analysis (EDA)?
Exploratory Data Analysis refers to the critical process of performing initial investigations on data so as to discover patterns, spot anomalies, test hypotheses and check assumptions with the help of summary statistics and graphical representations. The objectives of EDA are to:
- Enable unexpected discoveries in the data
- Suggest hypotheses about the causes of observed phenomena
- Assess assumptions on which statistical inference will be based
- Support the selection of appropriate statistical tools and techniques
- Provide a basis for further data collection through surveys or experiments
Many EDA techniques have been adopted in data mining. They are also being taught to young students as a way to introduce them to statistical thinking.