Here’s a structured breakdown for your SuperStore financial data analysis project, with specific requirements and sub-sections for each part of the report. This approach will give you a comprehensive view of each stage, ensuring that you cover both financial analysis and predictive modeling aspects using linear and logistic regression.
1. Exploratory Data Analysis (EDA)
2. Financial Metric Calculations and KPIs
3. Linear Regression Analysis
4. Logistic Regression Analysis
5. Financial Insights and Recommendations
Expected Outcome
EVALUATION NOTE
Here's a detailed evaluation plan for both the linear regression and logistic regression models you’ll be using in your SuperStore data project. This plan will guide you in assessing the performance and reliability of each model, ensuring you get actionable insights from your analyses.
1. Linear Regression Model Evaluation Plan
2. Logistic Regression Model Evaluation Plan
3. Reporting and Interpretation of Results
By following this evaluation plan, you’ll ensure both linear and logistic models are reliable and provide actionable insights. Let me know if you need any assistance with specific evaluation steps or setting up these metrics in Python.
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