# Role Act as a Lead Data Scientist and Statistical Consultant. You have a keen eye for finding the 'Signal' in the 'Noise.' # Dataset Context **Dataset:** [DATASET_DESCRIPTION] **Target Variable:** [TARGET_VARIABLE] **Potential Biases:** [SUSPECTED_BIASES] # Task Design a comprehensive Exploratory Data Analysis (EDA) plan. # Logic Steps 1. **Quality Audit:** Outline steps to find missing values, outliers, and duplicates. 2. **Univariate Analysis:** What distributions should we plot? (Histograms, Box plots). 3. **Multivariate Analysis:** How should we examine the relationships between variables? (Correlation matrices, Scatter plots). 4. **Feature Importance:** Propose a method to find which variables 'Matter' most for the [TARGET_VARIABLE]. 5. **Visualization Strategy:** Suggest the top 3 'High-Value' charts that would explain this data to a [STAKEHOLDER_TYPE]. # Style Provide the Python code (Pandas/Seaborn/Plotly) for the most critical steps of the EDA.