Introduction
- Getting to know each other.
- An overview of the lesson structure and objectives.
Graph Categories
- Scatter plots, bubble charts, heatmaps and correlograms for exploring relationships between two or more features.
- Bar charts and line charts for comparing different measures or trends.
- Histograms and box plots for exploring distributions.
- Pie charts and stacked bar charts for drawing comparisons.
Statistical Inference
- The concept of statistical inference.
- The difference between descriptive and inferential statistics.
- The concepts of correlation, regression and causation.
Data Visualization with Python for Statistical Inference and Storytelling
- Draw scatter plots, bubble charts and correlograms in Python, using the Seaborn library.
- Implement data visualization for exploratory analysis of a concrete dataset and telling a story based on the trends that it reveals.
- Use data visualization to infer information from a concrete dataset.
Conclusion
- Explore the possibilities of data visualization for statistical inference and storytelling.
- Figure out the next learning steps.