Data Analysis: Statistical Modeling and Computation in Applications

A hands-on introduction to the interplay between statistics and computation for the analysis of real data. -- Part of the MITx MicroMasters program in Statistics and Data Science.

Syllabus

Model, form hypotheses, perform statistical analysis on real data
Use dimension reduction techniques such as principal component analysis to visualize high-dimensional data and apply this to genomics data
Analyze networks (e.g. social networks) and use centrality measures to describe the importance of nodes, and apply this to criminal networks
Model time series using moving average, autoregressive and other stationary models for forecasting with financial data
Use Gaussian processes to model environmental data and make predictions
Communicate analysis results effectively