Can you explain the difference between exploratory data analysis and confirmatory data analysis?

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Answered by suresh

Exploratory Data Analysis vs. Confirmatory Data Analysis

Exploratory Data Analysis vs. Confirmatory Data Analysis

Exploratory Data Analysis (EDA) and Confirmatory Data Analysis (CDA) are two important methods in data analysis. Here's the difference between the two:

Exploratory Data Analysis

  • Exploratory Data Analysis is the initial phase of data analysis where the main focus is on summarizing the main characteristics of the data and gaining insights through visualizations and simple statistical techniques.
  • EDA is used to understand the nature of the data, detect patterns, identify outliers, and generate hypotheses for further analysis.
  • It is more flexible and iterative in nature, allowing data analysts to explore the data without preconceived notions.

Confirmatory Data Analysis

  • Confirmatory Data Analysis, on the other hand, is a hypothesis-driven approach where specific hypotheses are tested using formal statistical methods.
  • CDA aims to confirm or refute existing theories or hypotheses based on the data collected.
  • It is more structured and follows a predefined plan of analysis to validate or reject a specific hypothesis.

In summary, EDA is used for data exploration and hypothesis generation, while CDA is used for hypothesis testing and validation.

Answer for Question: Can you explain the difference between exploratory data analysis and confirmatory data analysis?