Phase 2: Statistics for Clinical Research using Python

Fundamental AI for clinical students.Basic Python for Clinical Students. Getting Started with Python Programming for Clinical Applications

1. Phase 2: Statistics for Clinical Research using Python Applying Python for statistical analysis in medicine

2. Objectives - Understand basic and advanced statistics for clinical research - Visualize data distributions and relationships - Apply hypothesis testing methods - Conduct survival analysis with real patient data

3. Topics - Descriptive statistics (mean, median, SD, percentiles) - Data visualization (matplotlib, seaborn, plotly) - Hypothesis testing (t-test, chi-square, ANOVA) - Correlation & regression basics - Survival analysis (Kaplan-Meier, log-rank test)

4. Practical Examples - Compare lab values between patient groups - Plot Kaplan-Meier survival curves for AMI patients

5. Suggested Tools - pandas, numpy for data analysis - matplotlib, seaborn for visualization - lifelines, statsmodels for survival and regression