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This tutorial will give users an overview of the capabilities of statsmodels, including how to conduct exploratory data analysis, fit statistical models, and check that the modeling assumptions are met.

The use of Python in data analysis and statistics is growing rapidly. It is not uncommon now for researchers to conduct data cleaning steps in Python and then move to some other software to estimate statistical models. Statsmodels, however, is a Python module that attempts to bridge this gap and allow users to estimate statistical models, perform statistical tests, and conduct data exploration in Python. Researchers across fields such as economics and the social sciences to finance and engineering may find that statsmodels meets their needs for statistical computing and data analysis in Python.

All examples in this tutorial will use real data. Attendees are expected to have some familiarity with statistical methods.

With this knowledge attendees will be ready to jump in and use Python for applied statistical analysis and will have an idea how they can extend statsmodels for their own needs.


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