The cumulative distribution function
Working with distributions
The probability density function
Where do models come from?
Multivariate distributions
Summary
4. Regression
Introducing linear regression
Getting the dataset
Testing with linear regression
Multivariate regression
Adding economic indicators
Taking a step back
Logistic regression
Some notes
Summary
5. Clustering
Introduction to cluster finding
Starting out simple – John Snow on cholera
K-means clustering
Suicide rate versus GDP versus absolute latitude
Hierarchical clustering analysis
Reading in and reducing the data
Hierarchical cluster algorithm
Summary
6. Bayesian Methods
The Bayesian method
Credible versus confidence intervals
Bayes formula
Python packages
U.S. air travel safety record
Getting the NTSB database
Binning the data
Bayesian analysis of the data
Binning by month
Plotting coordinates
Cartopy
Mpl toolkits – basemap
Climate change - CO2 in the atmosphere
Getting the data
Creating and sampling the model
Summary
7. Supervised and Unsupervised Learning
