This project uses the sashelp.heart dataset to study heart health, identify risk factors for heart disease, examine mortality causes and trends, and explore relationships among key variables. The goal is to derive insights and recommendations that can help improve heart health. For more details about the project please check the protocol in th main.
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Project Components
1. Data Preparation: Import and Cleaning: Load the dataset, handle missing values, and address data inconsistencies. Exploratory Data Analysis (EDA): Examine data distributions and identify potential outliers.
2. Statistical Analysis: Correlation Analysis: Explore relationships among numerical variables like age, cholesterol, and blood pressure. Comparative Analysis: Use t-tests or chi-square tests to compare groups (e.g., smokers vs. non-smokers). Regression Analysis: Build logistic regression models to predict heart disease risk. Survival Analysis: Examine factors affecting survival and mortality trends.
3. Visualization: Create visualizations like scatter plots, box plots, and histograms to understand data patterns. Generate survival curves to visualize differences in survival based on factors like gender and smoking.
4. Reporting and Recommendations: Summarize key findings from the analysis. Provide recommendations for improving heart health based on the results. Identify areas for further research and discuss any limitations.
Getting Started: Clone the repository from GitHub. Open the SAS project file or script. Follow the steps for data preparation, statistical analysis, and visualization. Review the output and share feedback or additional insights.
Collaboration Guidelines: Contributions: Use branches and submit pull requests for review. Code Reviews: Provide constructive feedback and suggest improvements. Issue Tracking: Use GitHub Issues to report bugs or suggest new features.
Additional Information: Refer to SAS documentation for more details on the dataset and SAS procedures. Explore statistical resources to deepen your understanding of the analyses used in this project.