The scientific method used in data science includes the following steps:
- Ask a Question: Clearly define the problem or phenomenon you want to study.
- Background Research: Review relevant literature to understand existing findings.
- Formulate Hypothesis: Based on background research, propose testable hypotheses.
- Collect Data: Gather relevant data from various sources, ensuring it is representative.
- Analyze Data: Use statistical methods and machine learning techniques for analysis, including exploratory data analysis (EDA).
- Interpret Results: Compare the analysis results with the hypotheses to determine support or refutation.
- Draw Conclusions: Summarize findings and discuss their significance and limitations.
- Communicate Results: Present your research outcomes through reports and visualizations.
- Iterate and Improve: Optimize questions and methods based on feedback and new discoveries.
This process helps data scientists apply a rigorous approach to solve complex problems.
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